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  Subjects -> METEOROLOGY (Total: 113 journals)
Showing 1 - 36 of 36 Journals sorted alphabetically
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 45)
Advances in Climate Change Research     Open Access   (Followers: 39)
Advances in Meteorology     Open Access   (Followers: 28)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 10)
Aeolian Research     Hybrid Journal   (Followers: 6)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 20)
American Journal of Climate Change     Open Access   (Followers: 34)
Atmósfera     Open Access   (Followers: 3)
Atmosphere     Open Access   (Followers: 29)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 13)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 48)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 16)
Atmospheric Environment     Hybrid Journal   (Followers: 75)
Atmospheric Environment : X     Open Access   (Followers: 3)
Atmospheric Research     Hybrid Journal   (Followers: 71)
Atmospheric Science Letters     Open Access   (Followers: 40)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 32)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Bulletin of the American Meteorological Society     Open Access   (Followers: 51)
Carbon Balance and Management     Open Access   (Followers: 5)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Climate     Open Access   (Followers: 6)
Climate and Energy     Full-text available via subscription   (Followers: 7)
Climate Change Economics     Hybrid Journal   (Followers: 33)
Climate Change Responses     Open Access   (Followers: 18)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Climate of the Past (CP)     Open Access   (Followers: 5)
Climate of the Past Discussions (CPD)     Open Access  
Climate Policy     Hybrid Journal   (Followers: 51)
Climate Research     Hybrid Journal   (Followers: 6)
Climate Resilience and Sustainability     Open Access   (Followers: 21)
Climate Risk Management     Open Access   (Followers: 7)
Climate Services     Open Access   (Followers: 3)
Climatic Change     Open Access   (Followers: 68)
Current Climate Change Reports     Hybrid Journal   (Followers: 10)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 31)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 9)
Energy & Environment     Hybrid Journal   (Followers: 24)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 17)
Frontiers in Climate     Open Access   (Followers: 3)
GeoHazards     Open Access   (Followers: 2)
Global Meteorology     Open Access   (Followers: 18)
International Journal of Atmospheric Sciences     Open Access   (Followers: 23)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 27)
International Journal of Climatology     Hybrid Journal   (Followers: 30)
International Journal of Environment and Climate Change     Open Access   (Followers: 12)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Journal of Agricultural Meteorology     Open Access  
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 36)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 34)
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 210)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 22)
Journal of Climate     Hybrid Journal   (Followers: 57)
Journal of Climate Change     Full-text available via subscription   (Followers: 16)
Journal of Climatology     Open Access   (Followers: 3)
Journal of Hydrology and Meteorology     Open Access   (Followers: 36)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 17)
Journal of Space Weather and Space Climate     Open Access   (Followers: 28)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 84)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Mediterranean Marine Science     Open Access   (Followers: 1)
Meteorologica     Open Access   (Followers: 2)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Meteorological Monographs     Hybrid Journal   (Followers: 2)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 27)
Mètode Science Studies Journal : Annual Review     Open Access  
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 16)
Monthly Weather Review     Hybrid Journal   (Followers: 33)
Nature Climate Change     Full-text available via subscription   (Followers: 144)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 39)
Nīvār     Open Access  
npj Climate and Atmospheric Science     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 4)
Open Journal of Modern Hydrology     Open Access   (Followers: 7)
Revista Brasileira de Meteorologia     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Space Weather     Full-text available via subscription   (Followers: 25)
Studia Geophysica et Geodaetica     Hybrid Journal  
Tellus A     Open Access   (Followers: 22)
Tellus B     Open Access   (Followers: 21)
The Cryosphere (TC)     Open Access   (Followers: 6)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 28)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Tropical Cyclone Research and Review     Open Access  
Urban Climate     Hybrid Journal   (Followers: 4)
Weather     Hybrid Journal   (Followers: 18)
Weather and Climate Dynamics     Open Access  
Weather and Climate Extremes     Open Access   (Followers: 16)
Weather and Forecasting     Hybrid Journal   (Followers: 27)
Weatherwise     Hybrid Journal   (Followers: 4)
气候与环境研究     Full-text available via subscription   (Followers: 1)

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Advances in Meteorology
Journal Prestige (SJR): 0.48
Citation Impact (citeScore): 1
Number of Followers: 28  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-9309 - ISSN (Online) 1687-9317
Published by Hindawi Homepage  [343 journals]
  • Seasonal Changes in Climate Variables in Rainfed Crop Areas in the
           Lerma-Chapala-Santiago Basin, Mexico

    • Abstract: This paper shows the effects of changes in the spatial-temporal behavior and phase shift of climate variables on rainfed agriculture in the Lerma-Chapala-Santiago Basin in central Mexico. Specifically, changes in rainfall (R), maximum temperature (Tmax), and minimum temperature (Tmin) were analyzed over two 25-year periods (1960 to 1985 and 1986 to 2010). Climate surfaces were generated by interpolation using the thin-plate smoothing spline algorithm in the software ANUSPLIN. Climate data were Fourier-transformed and fitted to a sinusoidal curve model, and changes in amplitude (increase) and phase were analyzed. The temporal behavior (1960–2010) indicated that rainfall was the most stable variable at the monthly level and presented no significant changes. However, Tmax increased by 2°C in the final period, and Tmin increased by 0.7°C at the end of the final period. The basin was discretized into ten rainfed crop areas (RCAs) according to the extent of changes in the amplitude and phase of the climate variables. The central and southern portions (55% of the area) presented more significant changes in amplitude, mainly in Tmin and Tmax. The remaining RCAs were smaller (14.6%) but presented greater variation: the amplitude of the Tmin decreased in addition to showing a phase shift, whereas Tmax increased in addition to showing a phase shift. These results translate into a delay in the characteristic temperatures of the spring and summer seasons, which can impact the rainfed crop cycle. Additionally, rainfall showed an annual decrease of approximately 50 mm in all RCAs, which can affect the phenological development of crops during critical stages (emergence through flowering). These changes represent a significant threat to the regional economy and food security of Mexico.
      PubDate: Wed, 13 Oct 2021 06:20:01 +000
  • Drought and Wetness Variability and the Respective Contribution of
           Temperature and Precipitation in the Qinghai-Tibetan Plateau

    • Abstract: Quantifying drought and wetness fluctuations is of great significance to the regional ecological environment and water resource security, especially in the fragile Qinghai-Tibetan Plateau (QTP). In this paper, the standardized precipitation evapotranspiration index (SPEI) was calculated based on the observed data and China Meteorological Forcing Dataset (CMFD) in the QTP for the period of 1979–2015, and the drought and wetness evolution based on the SPEI series and respective contribution of temperature and precipitation were also analyzed. Results indicated that meteorological stations are mainly concentrated in the eastern part of the plateau, which cannot reflect the drought and wetness trend of the whole QTP. The linear trend and Mann–Kendall test revealed that SPEI series calculated based on CMFD data at 1-, 3-, 6-, 9-, 12-, and 24-month time scales all showed significant upward trend , indicating that the QTP as a whole tended to be wetter. Spatially, the regions with significant drying and increased drought probability were mainly concentrated in the Qaidam Basin and the southern part of the QTP, and the mean contribution rates of temperature and precipitation variability to SPEI trend in these regions were 60% and −11%, respectively. The regions with significant wetting and decreased drought probability were mainly concentrated in the northeast, central, and western parts of the plateau, and the mean contribution rates of temperature and precipitation variability to SPEI trend were −9% and 61% in these regions. From the statistics in different climatic regions, most of the arid and humid regions in the QTP tended to be drier, while the semiarid regions tended to be wetter.
      PubDate: Wed, 29 Sep 2021 05:50:00 +000
  • Convective Cold Pool Associated with Offshore Propagation of Convection
           System over the East Coast of Southern Sumatra, Indonesia

    • Abstract: The cold pool outflow has been previously shown to be generated by decaying Mesoscale Convective Complexes (MCCs) in the Maritime Continent. The cold pool also has a main role in the development processes of oceanic convective systems inducing heavy rainfall. This study investigated a cold pool event (January 1-2, 2021) related to a heavy rainfall system over the coastal region of Lampung, Southern Sumatra, within a high-resolution model simulation using a regional numerical weather prediction of the Weather Research and Forecasting (WRF) with convection permitting of 1 km spatial resolution, which was validated by satellite and radar data observations. It is important to note that the intensity, duration, timing, and structure of heavy rainfall simulated were in good agreement with satellite-observed rainfall. The results also showed that a cold pool (CP) plays an important role in inducing Mesoscale Convective Complex (MCC) and was responsible for the development of an offshore propagation of land-based convective systems due to the late afternoon rainfall over inland. This study also suggests that the propagation speed of the CP 8.8 m·s−1 occurring over the seaside of the coastal region, the so-called CP-coastal, is a plausible mechanism for the speed of the offshore-propagating convection, which is dependent on both the background prevailing wind and outflow. These conditions help to maintain the near-surface low temperatures and inhibit cold pool dissipation, which has implications for the development of consecutive convection.
      PubDate: Tue, 28 Sep 2021 11:35:01 +000
  • Accuracy Evaluation and Parameter Analysis of Land Surface Temperature
           Inversion Algorithm for Landsat-8 Data

    • Abstract: Many researchers have developed a variety of land surface temperature (LST) inversion algorithms based on satellite data. The main LST inversion algorithms include Radiative Transfer Equation (RTE), Single Channel (SC) algorithm, Mono Window (MW) algorithm, and Split Window (SW) algorithm. In this study, nine LST inversion algorithms were designed using Landsat-8 data and meteorological station data to test the inversion efficiency of different algorithms in different seasons and different locations. The results show that the error of various LST inversion algorithms will increase with the rise of LST. R2 of the inversion results of each LST algorithm and the measured data are all greater than 0.73°C in winter and about 0.5°C in the other seasons. By analyzing the stability of various algorithms inside and outside the city, it is found that the stability of each LST inversion algorithm inside the city is better than that outside the city. For the same surface features, the inversion temperature inside the city is 3–5°C higher than that outside the city. In addition, the sensitivity of various inversion algorithms to parameters was also analyzed. The influence of atmospheric transmittance on RTE, SC, and MW inversion algorithms is in logarithmic form. The effect of emissivity on each algorithm is linear. The influence of NDVI on the algorithms is mainly through the estimation of surface emissivity parameters to affect the inversion results. The effect of ascending radiation on SC (LST4 and LST5) is linear and on RTE (LST1 and LST2) is logarithmic. The effect of downslope radiation on SC and RTE is linear. The influence of atmospheric water vapor content on SW (LST7) is nonlinear.
      PubDate: Fri, 24 Sep 2021 12:20:00 +000
  • Comparison of Multiple Surface Ocean Wind Products with Buoy Data over
           Blue Amazon (Brazilian Continental Margin)

    • Abstract: Remote sensing data for space-time characterization of wind fields in extensive oceanic areas have been shown to be increasingly useful. Orbital sensors, such as radar scatterometers, provide data on ocean surface wind speed and direction with spatial and temporal resolutions suitable for multiple applications and air-sea studies. Even considering the relevant role of orbital scatterometers to estimate ocean surface wind vectors on a regional and global scale, the products must be validated regionally. Six different ocean surface wind datasets, including advanced scatterometer (ASCAT-A and ASCAT-B products) estimates, numerical modelling simulations (BRAMS), reanalysis (ERA5), and a blended product (CCMP), were compared statistically with in situ measurements obtained by anemometers installed in fifteen moored buoys in the Brazilian margin (8 buoys in oceanic and 7 in shelf waters) to analyze which dataset best represents the wind field in this region. The operational ASCAT wind products presented the lowest differences in wind speed and direction from the in situ data (0.77 ms−1 
      PubDate: Tue, 14 Sep 2021 12:05:01 +000
  • Corrigendum to “The Impact of Tropical Cyclones in Premonsoonal Season
           on Local Convection over the Al-Hajar Mountains in Oman during

    • PubDate: Sat, 11 Sep 2021 05:20:02 +000
  • Carbon Dioxide Emission Measurement and Its Spatiotemporal Evolution of
           Tourism Industry in Heilongjiang Province, China

    • Abstract: This study analyses the composition and evolution of carbon dioxide emissions from the tourism industry in Heilongjiang Province and its 12 regions by the tourism consumption stripping coefficient method and calculates the decoupling relationship between the carbon dioxide emissions and economic growth of tourism from 2010 to 2019. The empirical results are as follows. (1) From 2010 to 2019, carbon dioxide emissions from Heilongjiang Province’s tourism industry and its subsector increased steadily, of which the tourism industry accounted for a relatively large amount of carbon dioxide emissions in “Transport, Storage, and Post.” (2) Time series analysis reveals that the carbon dioxide emissions of tourism basically show an increasing trend and there are still multiple decoupling relationships with economic growth. Expansive decoupling and weak decoupling have occurred more frequently. (3) Spatial analysis reveals that the carbon dioxide emissions of the regional tourism industry show a fluctuating upward trend. The tourism industry in Harbin has significantly higher carbon dioxide emissions than in other regions. In addition, this study provides feasible suggestions and countermeasures for low-carbon tourism development in Heilongjiang Province. The findings are considered useful in future planning of energy conservation and emission reduction in Heilongjiang Province and the regional tourism industry.
      PubDate: Fri, 03 Sep 2021 07:05:01 +000
  • Evaluation of Seven Gap-Filling Techniques for Daily Station-Based
           Rainfall Datasets in South Ethiopia

    • Abstract: Meteorological stations, mainly located in developing countries, have gigantic missing values in the climate dataset (rainfall and temperature). Ignoring the missing values from analyses has been used as a technique to manage it. However, it leads to partial and biased results in data analyses. Instead, filling the data gaps using the reference datasets is a better and widely used approach. Thus, this study was initiated to evaluate the seven gap-filling techniques in daily rainfall datasets in five meteorological stations of Wolaita Zone and the surroundings in South Ethiopia. The considered gap-filling techniques in this study were simple arithmetic means (SAM), normal ratio method (NRM), correlation coefficient weighing (CCW), inverse distance weighting (IDW), multiple linear regression (MLR), empirical quantile mapping (EQM), and empirical quantile mapping plus (EQM+). The techniques were preferred because of their computational simplicity and appreciable accuracies. Their performance was evaluated against mean absolute error (MAE), root mean square error (RMSE), skill scores (SS), and Pearson’s correlation coefficients (R). The results indicated that MLR outperformed other techniques in all of the five meteorological stations. It showed the lowest RMSE and the highest SS and R in all stations. Four techniques (SAM, NRM, CCW, and IDW) showed similar performance and were second-ranked in all of the stations with little exceptions in time series. EQM+ improved (not substantial) the performance levels of gap-filling techniques in some stations. In general, MLR is suggested to fill in the missing values of the daily rainfall time series. However, the second-ranked techniques could also be used depending on the required time series (period) of each station. The techniques have better performance in stations located in higher altitudes. The authors expect a substantial contribution of this paper to the achievement of sustainable development goal thirteen (climate action) through the provision of gap-filling techniques with better accuracy.
      PubDate: Thu, 19 Aug 2021 08:05:00 +000
  • Characteristics of Raindrop Size Distribution in Typhoon Nida (2016)
           before and after Landfall in Southern China from 2D Video Disdrometer Data

    • Abstract: During the passage of Typhoon Nida, the raindrop size distribution parameters, the raindrop spectra, the shape and slope (μ–Λ) relationship, the radar reflectivity factor, and rain rate (Z–R) relationship were investigated based on a two-dimensional (2D) video disdrometer in Guangdong, China, from August 1 to 2, 2016. Due to the underlying surface difference between the ocean and land, this process was divided into two distinct periods (before landfall and after landfall). The characteristics of raindrop size distribution between the period before landfall and the period after landfall were quite distinct. The period after landfall exhibited higher concentrations of each size bin (particularly small drops) and wider raindrop spectral width than the period before landfall. Compared with the period before landfall, the period after landfall had a higher average mass-weighted mean diameter Dm that was smaller than those of other TCs from the same ocean (the Pacific). The μ–Λ relationship and Z–R relationship in this study were also compared with other TCs from the same ocean (the Pacific). This investigation of the microphysical characteristics of Typhoon Nida before landfall and after landfall may improve radar quantitative precipitation estimation (QPE) products and microphysical schemes by providing useful information.
      PubDate: Thu, 12 Aug 2021 09:35:07 +000
  • Contribution Degree of Different Surface Factors in Urban Interior to
           Urban Thermal Environment

    • Abstract: The contribution degree of different surface factors (complexity and heterogeneity) in the urban interior to the urban thermal environment has become an issue of increasing concern under changing climate. In this paper, the multiple linear regression analysis methods to analyze the contribution degree of different surface factors to the urban thermal environment were based on seven urban built-up areas. At the same time, the LST of the same type of factors in the same city will have a difference of ±2.5°C due to the different surrounding features. At the same time, the LST of the same ground object in the same city will be ±2.5°C different because of the difference of the surrounding ground object. The environmental LST and the mean LST of other surface factors were significantly correlated, and the root mean square error was 3.52. This study first classifies the ground features with different attributes, conducts LST statistics for each category, and conducts multivariate linear analysis, instead of setting some fuzzy exponent and forcing a threshold to calculate. The purpose is to explore the contribution of different reflectivity ground objects to the urban thermal environment.
      PubDate: Thu, 12 Aug 2021 07:20:09 +000
  • Dependence of Warm Season Cloud-to-Ground Lightning Polarity on
           Environmental Conditions over Sichuan, Southwest China

    • Abstract: The effects of thermodynamic and moisture factors on cloud-to-ground (CG) lightning polarity in the warm season were discussed. Small convective available potential energy (CAPE) represents relatively shallow convection, which is beneficial to the generation of positive lightning. Large vertical wind shear results in the displacement of upper-level positive ice crystals and promotes the initiation of +CG lightning from positive ice crystals. The dry low- to midlevel troposphere and the high cloud base in the plateau region favor +CG lightning, while the strong thermodynamic conditions in the basin region offset the influence of these moisture factors. In the plateau region, due to the limited cloud thickness, high total column liquid water may mean high cloud water content in the warm cloud region rather than high liquid water content in the mixed-phase region, which is unfavorable for the middle-level positive graupel and thus is unfavorable for the initiation of +CG lightning. In the basin region, the cloud thickness is relatively thicker, the high total column liquid water means that the liquid water content in the warm cloud and the mixed-phase region is both high, which is conducive to the middle-level positive graupel and the +CG lightning.
      PubDate: Tue, 03 Aug 2021 10:50:02 +000
  • Offline Single-Polarization Radar Quantitative Precipitation Estimation
           Based on a Spatiotemporal Deep Fusion Model

    • Abstract: Quantitative precipitation estimation (QPE) based on Doppler radar plays an important role in severe weather monitoring, industrial and agricultural production, and natural disaster prediction and prevention. However, the temporal and spatial variability of precipitation leads to large errors in radar estimates of mixed precipitation. To improve the accuracy of radar QPE, we propose an offline spatiotemporal deep fusion model that uses the reflectivity data of the Shijiazhuang Doppler radar Z9311 and the precipitation data from 17 national weather stations (NWSs) and 260 automatic weather stations (AWSs). Considering the abrupt spatial changes in precipitation, a three-dimensional radar data structure is proposed, and the spatial features of multielevation and multiscale radar data are extracted and merged using the feature fusion network (FFNet). Finally, the time dependence of the precipitation is captured using the long short-term memory (LSTM) network, and the precipitation estimation is obtained. Based on a comparison of the results of the proposed model (FFNet-LSTM) with those of the ordinary kriging (OK) interpolation, two Z-R relationship, the multilayer perceptron (MLP), the LSTM, and the FFNet, the proposed method is superior to these models, has a promising performance, and is a general-purpose rainfall algorithm.
      PubDate: Wed, 28 Jul 2021 06:05:01 +000
  • Spatial Variability and Temporal Trends of Climate Change in Southwest
           Ethiopia: Association with Farmers’ Perception and Their Adaptation

    • Abstract: The impact of climate change is a global threat, and its effect is more pronounced in developing countries. It is vital to link physical data analysis with endogenous knowledge and practices of farmers to strengthen their adaptive capacity. This study was conducted to explore spatial variability and temporal trends of temperature and rainfall in association with farmers’ perceptions and their adaptation strategies in Southwest Ethiopia. Daily rainfall and temperature data of twelve weather stations were collected from the National Meteorological Agency of Ethiopia for the period 1983 to 2016. Farmers’ perceptions about climate change and its impact and their adaptation strategies were assessed through a survey. Spatial variability and temporal trends of rainfall and temperature were analyzed using ArcGIS and R software. Sen’s slope estimator and Mann–Kendall’s trend tests were used to detect the magnitude and statistical significance of changes in rainfall and temperature. Spatial analysis of rainfall showed high variability over the region. There were no consistent and significant temporal trends of annual and seasonal rainfall of the area. Significant and upward trends of annual maximum and minimum temperatures were reported for all stations. Accordingly, annual maximum and minimum temperatures were increased by 0.71 and 0.65°C, respectively, over the period 1983 to 2016. Farmers had a good awareness of climate change and its impact. Adaptation strategies used by farmers included soil and water conservation practices (66.21%), crop diversification (62.16%), modifying planting date (42.56%), agroforestry practices (35.13%), use of drought-tolerant variety (33.95%), use of early maturing crop (27.03%), and livelihood diversification (25.42%). As most of these adaptation strategies were familiarized by a small number of farmers, further effort is needed to identify factors limiting the adoption of these strategies. Furthermore, additional planned strategies and supports that widen available options at the farmers’ disposal should be introduced to strengthen their adaptive capacity.
      PubDate: Mon, 26 Jul 2021 06:20:01 +000
  • Towards Healthy Levels of Carbon Dioxide in Schools of the National Oil
           Company of Abu Dhabi

    • Abstract: In their annual indoor air quality assessment for ADNOC Schools, the Abu Dhabi Education Council has reported hazardous levels (∼3000 ppm) of carbon dioxide in fifteen classrooms. Exposure of 5,090 students attending the school for ∼eight hours (typical school day) to such high levels of carbon dioxide would induce adverse health conditions like headaches, drowsiness, and lack of concentration on the short term and serious diseases like asthma and sick building syndrome on the long term. The Health, Safety, and Environment committee of the school has identified clogged air intake vents and dirty AC filters as the main cause of the high carbon dioxide concentrations reported. The outdoor (ambient) carbon dioxide level is measured and has an eight-hour average value of 419 ppm. After cleaning thoroughly, the indoor levels of carbon dioxide, temperature, and relative humidity were monitored simultaneously in each classroom and have average values of ∼1117 ppm, ∼24°C, and ∼37%, respectively. In addition, the average indoor-to-outdoor ratio of carbon dioxide has been improved from before cleaning the AC filters to an average ratio of () after cleaning. Thus, ventilation rates in the classrooms monitored in this project are adequate and the corrective actions taken were effective.
      PubDate: Thu, 22 Jul 2021 12:20:01 +000
  • Corrigendum to “A Spatial Interpolation of Meteorological Parameters
           considering Geographic Semantics”

    • PubDate: Mon, 12 Jul 2021 06:05:01 +000
  • Potential Source Regions and Transportation Pathways of Reactive Gases at
           a Regional Background Site in Northwestern China

    • Abstract: Reactive gases (O3, CO, NO2, and SO2) were collected hourly at the Akedala regional background station in northwestern China during September 2017 to August 2018. Wind rose, cluster analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) methods were adopted for identifying the transport pathways and potential source regions of these atmosphere components at Akedala. The average O3, CO, NO2, and SO2 mixing ratios detected were 29.65 ± 11.44 ppb, 123.78 ± 73.35 ppb, 3.79 ± 0.98 ppb, and 4.59 ± 0.88 ppb during the observation period, and the statistical results of the monthly mean values revealed that there were differences during the highest pollution period, with O3 and CO mainly peaking in February, with mixing ratios of 38.03 ± 7.10 ppb and 208.50 ± 106.50 ppb, respectively. Meanwhile, NO2 peaked in March (4.51 ± 0.54 ppb) and SO2 in January (5.70 ± 1.92 ppb). The most obvious diurnal variation of CO and SO2 was observed in the winter, with maximum levels reaching between 13 : 00 and 14 : 00. The diurnal variations of O3 exhibited low values during the night and maximum values in the afternoon (16 : 00–18 : 00). Diurnal variation was not significant in the case of NO2. Cluster analysis showed that six main paths affected the Akedala atmosphere. In turn, the PSCF and CWT analysis results indicated that the Akedala reactive gas was affected by both local and foreign sources. The high PSCF value of the reactive gas potential source areas appeared in eastern Kazakhstan, northern Xinjiang, Western Mongolia, and Southern Russia. The WCWT (weighted concentration-weight trajectory) values of CO and SO2 in winter were the highest, totaling 180–240 ppb and 5–6.5 ppb, respectively. The WCWT value of O3 in the spring and summer was higher than that in the autumn and winter. The main source area of O3 was about 32–36 ppb in the spring and summer, and the main source area of NO2 in the summer had a low WCWT value of 3–3.5 ppb, whereas the NO2 WCWT value was concentrated at 4–4.5 ppb in the other seasons.
      PubDate: Sat, 03 Jul 2021 05:35:01 +000
  • Characteristics and Meteorological Factors of Severe Haze Pollution in

    • Abstract: A severe haze pollution incident caused by unfavorable weather conditions and a northern air mass occurred in eastern, northern, northwestern, and southwestern China from January 15 to January 22, 2018. To comparatively analyze variations in PM2.5 pollution, hourly monitoring data and 24 h meteorological data were collected. Air quality observations revealed large spatiotemporal variation in PM2.5 concentrations in Handan, Zhengzhou, Xi’an, Yuncheng, Chengdu, Xiangyang, and Jinan. The daily mean PM2.5 concentrations ranged from 111.35 to 227.23 μg·m−³, with concentration being highest in Zhengzhou. Hourly mean PM2.5 concentration presented multiple U-shaped curves, with higher values at night and lower values during the day. The ratios of PM2.5 to PM10 were large in target cities and the results of multiscale geographic weighted regression model (MGWR) and Pearson correlation coefficients showed that PM2.5 had a significant positive or negative correlation with PM10, CO, NO2, and SO2. The concentration of PM2.5 was closely related to the combustion of fossil fuels and other organic compounds, indicating the large contribution of secondary aerosols to PM2.5 concentrations. The analysis of meteorological conditions showed that low temperature, low wind speed, and high relative humidity could aggravate the accumulation of regional pollutants in winter. Northwestern trajectory clusters were predominant contributions except in Jinan, and the highest PM2.5 concentrations in target cities were associated with short trajectory clusters in winter. The potential sources calculated by Weight Potential Source Contribution Function (WPSCF) and Weight Concentration-Weighted Trajectory (WCWT) models were similar and the highest values of the WPSCF (>0.5) and the WCWT (>100 μg·m−³) were mainly distributed in densely populated, industrial, arid, and semiarid regions.
      PubDate: Tue, 22 Jun 2021 05:05:01 +000
  • Surface Layer Turbulent Characteristics over the Complex Terrain of the
           Loess Plateau Semiarid Region

    • Abstract: Surface layer turbulence has an important influence on land-air interactions and pollutant dispersion, and studying the characteristics of surface layer turbulence in complex terrain can contribute to understanding land-air interactions, improving model surface layer parameterization, and enhancing pollution prediction capabilities. The surface layer turbulence observations from the Semi-Arid Climate and Environment Observatory (SACOL) of Lanzhou University in 2008 were processed in this study. High-quality turbulence parameters were calculated, the statistical and transfer characteristics of turbulence were analyzed, and the formation of turbulence was assessed in terms of dynamics and thermodynamics. The atmospheric stability in the semiarid region of the Loess Plateau is basically dominated by neutral/near-neutral and weakly unstable/weakly stable conditions; this pattern is significantly different from the preponderance of unstable and stable layers at other sites. The turbulence intensity differs significantly in both the horizontal and vertical directions and basically shows the relationship . The mean values of and are 0.42 and 0.40, respectively, and the mean value of is 0.14, which is different from the general pattern of , indicating that the turbulence intensity at SACOL is characterized by a large lateral wind contribution. The dimensionless standard deviations of the nonneutral wind velocity components satisfy the “1/3rd law,” and the dimensionless standard deviations of u, , and components are 3.35, 2.98, and 1.26, respectively, in the semiarid Loess Plateau. These values are larger than those over flat terrain. The contribution of the shear term to the formation of turbulence is greater than that of the buoyancy term, and the mean annual values of the shear term and the buoyancy in the kinetic energy budget equation in SACOL are 47.94 × 10−4 m2·s−3 and 11.32 × 10−4 m2·s−3, respectively. The annual mean values of the momentum transfer coefficient and the heat transfer coefficient under near-neutral conditions are 8.54 × 10−3 and 2.52 × 10−3, respectively.
      PubDate: Sat, 12 Jun 2021 07:35:01 +000
  • A GA-Based BP Artificial Neural Network for Estimating Monthly Surface Air
           Temperature of the Antarctic during 1960–2019

    • Abstract: The spatial sparsity and temporal discontinuity of station-based SAT data do not allow to fully understand Antarctic surface air temperature (SAT) variations over the last decades. Generating spatiotemporally continuous SAT fields using spatial interpolation represents an approach to address this problem. This study proposed a backpropagation artificial neural network (BPANN) optimized by a genetic algorithm (GA) to estimate the monthly SAT fields of the Antarctic continent for the period 1960–2019. Cross-validations demonstrate that the interpolation accuracy of GA-BPANN is higher than that of two benchmark methods, i.e., BPANN and multiple linear regression (MLR). The errors of the three interpolation methods feature month-dependent variations and tend to be lower (larger) in warm (cold) months. Moreover, the annual SAT had a significant cooling trend during 1960–1989 (trend = −0.07°C/year; ) and a significant warming trend during 1990–2019 (trend = 0.06°C/year; ). The monthly SAT did not show consistent cooling or warming trends in all months, e.g., SAT did not show a significant cooling trend in January and December during 1960–1989 and a significant warming trend in January, June, July, and December during 1990–2019. Furthermore, the Antarctic SAT decreases with latitude and the distance away from the coastline, but the eastern Antarctic is overall colder than the western Antarctic. Spatiotemporal inconsistencies on SAT trends are apparent over the Antarctic continent, e.g., most of the Antarctic continent showed a cooling trend during 1960–1989 (trend = −0.20∼0°C/year; ) with a peak over the central part of the eastern Antarctic continent, while the entire Antarctic continent showed a warming trend during 1990–2019 (trend = 0∼0.10°C/year; ) with a peak over the higher latitudes.
      PubDate: Mon, 07 Jun 2021 11:35:01 +000
  • A Multiscale Assessment of Three Satellite Precipitation Products (TRMM,
           CMORPH, and PERSIANN) in the Three Gorges Reservoir Area in China

    • Abstract: This study evaluated three satellite precipitation products, namely, TRMM, CMORPH, and PERSIANN, over the Three Gorges Reservoir area in China at multiple timescales. The assessment covered the following aspects: the rainfall amount, extreme precipitation, and the rainy-day detection ability. Results indicated that the CMORPH and TRMM estimates of rainfall amount were reasonably good, but the PERSIANN showed a larger bias than the other two satellite products. The data precision of CMORPH was slightly better than TRMM. All three satellite products could reproduce the diurnal cycle of rainfall, i.e., more precipitation in the morning than in the evening. The CMORPH estimates were closest to the gauge observation at 3-hourly and 12-hourly timescales. The data accuracy of CMORPH data was better during the night than in the daytime. At daily timescale, the quality of TRMM data was slightly inferior to the CMORPH, whereas the PERSIANN still differed much from the ground observation. At monthly, seasonally, and yearly timescales, the performance of TRMM was comparable to CMORPH, and both of them were obviously superior to PERSIANN. The rainy-day detection ability of CMORPH and TRMM was much better than PERSIANN. The PERSIANN data tended to overestimate the light rainy days but underestimate the heavy and torrential rainy days. The CMORPH data overestimated mainly the moderate rainy days. The TRMM data overestimated the occurrence frequency of heavy rain during the winter half year (from October to the next March). Both the CMORPH and the TRMM provided good estimates of the regional average rainy days. The data accuracy of CMORPH was slightly better than TRMM, and both were far better than the PERSIANN with respect to the rainfall amount and rainy-day detection. Nevertheless, all satellite estimates showed large biases of extreme precipitation. The CMORPH estimate of the maximum 5-day precipitation was the best of all. Both the CMORPH and TRMM data overestimated the 95th percentile of precipitation, but the PERSIANN data severely underestimated it. The PERSIANN estimates of extreme precipitation amount were the best of all during the daytime, nighttime, and the whole day. The above evaluation results could facilitate the application of satellite rainfall products and provide a reference to precipitation-related studies.
      PubDate: Thu, 03 Jun 2021 08:50:02 +000
  • Periodic Cycles of Eyewall Convection Limit the Rapid Intensification of
           Typhoon Hato (2017)

    • Abstract: The ability to forecast tropical cyclone (TC) intensity has improved modestly in recent years, partly because of an inadequate understanding of eyewall convection processes. Short-term periodic convection activities (period: 3–5 h) have been identified in a number of TCs, but the effect of these activities on the evolution of TC intensity at the hourly scale is yet to be fully investigated. Using radar observations and a high-resolution numerical simulation based on the Weather Research and Forecasting model, we analyzed the periodic cycles of eyewall convection associated with the intensification of Typhoon Hato (2017). Results indicate the presence of four short-term periodic cycles (period: 3–5 h) in the eyewall convection, which correspond to TC intensification. We further divided each cycle into three stages. The periodic evolution of convection inhibited the rapid intensification of the TC. The highest and lowest intensification rates were associated with the first and third stages according to the virtual potential temperature tendency in the eyewall region, respectively. Heating was dominated by the vertical advection associated with sensible heat and latent heat, which were controlled by the eyewall convection and structure. Of the three stages in each cycle, the vertical transport released the largest amount of latent heat in the first stage; consequently, the highest intensification rate occurred in this stage. In the second stage, heating was reduced because of decreased latent heat and increased cooling of sensible heat associated with vertical advection as the eyewall intensified. Vertical transport was the weakest in the third stage; this resulted in the smallest amount of heating, which limited the rapid intensification of the TC.
      PubDate: Sun, 30 May 2021 12:05:01 +000
  • Observation and Simulation of Wind Speed and Wind Power Density over Bac
           Lieu Region

    • Abstract: In this study, the WRF (Weather Research and Forecasting) model was used to simulate and investigate diurnal and annual variations of wind speed and wind power density over Southern Vietnam at 2‐km horizontal resolution for two years (2016 and 2017). The model initial and boundary conditions are from the National Centers for Environmental Prediction (NCEP) Final Analyses (FNL). Observation data for two years at 20 m height at Bac Lieu station were used for model bias correction and investigating diurnal and annual variation of wind speeds. The results show that the WRF model overestimates wind speeds. After bias correction, the model reasonably well simulates wind speeds over the research area. Wind speed and wind power density show much higher values at levels of 50–200 m above ground levels than near ground (20 m) level and significantly higher near the coastal regions than inland. Wind speed has significant annual and diurnal cycles. Both annual and diurnal cycles of wind speeds were well simulated by the model. Wind speed is much stronger during daytime than at nighttime. Low-level wind speed reaches the maximum at about 14 LT to 15 LT when the vertical momentum mixing is highly active. Wind speeds over the eastern coastal region of Southern Vietnam are much stronger in winter than in summer due to two main reasons, including (1) stronger large-scale wind speed in winter than in summer and (2) funnel effect creating a local maximum wind speed over the nearshore ocean which then transports high-momentum air inland in winter.
      PubDate: Mon, 17 May 2021 08:20:00 +000
  • Long-Term Rainfall Information Forecast by Utilizing Constrained Amount of
           Observation through Artificial Neural Network Approach

    • Abstract: Estimating models are becoming increasingly crucial in highlighting the nonlinear connections of the massive level of rough information and chaotic components. The study demonstrates a modern approach utilizing a created artificial neural network (ANN) method that may be an alternative strategy to conventional factual procedures for advancing rainfall estimate execution. A case study was presented for Turkey’s Düzce and Bolu neighboring territories located on the Black Sea’s southern coast. This study’s primary aim is to create an ANN model unique in the field to generate satisfactory results even with limited data. The proposed technique is being used to estimate rainfall and make predictions regarding future precipitation. Bolu daily average rainfall by month data and a limited number of Düzce rainfall data were used. Missing forecasts and potential rainfall projections will be examined in the fundamental research. This research further focuses on ANN computational concepts and develops a neural network for rainfall time series forecasting. The emphasis of this study was a feed-forward backpropagation network. The Levenberg–Marquardt algorithm (LMA) was implemented for training a two-layer feed-forward ANN for the missing rainfall data prediction part of this research. The inaccessible rainfall parameters for Düzce were determined for the years 1995 to 2009. From 2010 to 2020, a two-layer feed-forward ANN was trained using the gradient descent algorithm to forecast daily average rainfall data by month. The findings reported in this study guide researchers interested in implementing the ANN forecast model for an extended period of missing rainfall data.
      PubDate: Thu, 06 May 2021 07:05:00 +000
  • Impacts of Air-Sea Energy Transfer on Typhoon Modelling

    • Abstract: The Coupled Ocean-Atmosphere-Wave-Sediment Transport model has been used to simulate Super Typhoon Yutu (2018). The impacts of four momentum transfer parameterization schemes (COARE, TY, OT, and DN) and three heat transfer parameterization schemes (COARE, GR, and ZK) on typhoon modelling have been studied by means of the track, intensity, and radial structure of typhoon. The results show that the track of Yutu is not sensitive to the choice of parameterization scheme, while the combinations of different parameterization schemes affect the intensity of Yutu. Among the four momentum flux parameterization schemes, three wave-state-based schemes (TY, OT, and DN) provide better intensity results than the wind-speed-based COARE scheme, but the differences between the three wave-state-based schemes are not obvious. Among the three heat flux parameterization schemes, the results of the GR scheme are slightly better than those of the COARE scheme, and both the GR and COARE schemes are significantly better than the ZK scheme, from which the intensity of Yutu is underpredicted obviously. The influence of the combination of different parameterization schemes on the intensity of the typhoon is also reflected in the radial structure of the typhoon, and the radial structure of the typhoon simulated by experiments with stronger typhoon intensity also develops faster. Differences of intensity between experiments are due mainly to the differences in sea surface heat flux, the enthalpy transferred from sea surface to the atmosphere has a significant impact on the bottom atmosphere wind field, and there is a strong correspondence between the distribution of enthalpy flux and the bottom wind field.
      PubDate: Thu, 15 Apr 2021 09:05:01 +000
  • Characteristics and Development Mechanisms of Northeast Cold Vortices

    • Abstract: The northeast cold vortices (NECVs) in May-September during 1989–2018 are classified, based on the 6 h NCEP/NCAR reanalysis data (2.5° × 2.5°) and observational data from the Meteorological Information Comprehensive Analysis and Process System (MICAPS) provided by China Meteorological Administration. Meanwhile, characteristics and development mechanisms for NECVs of different types are also analyzed. In the recent 30 years, the occurrences of NECV processes have been increasing year by year, with an average of 7.4 times per year in Northeast China and a duration of 3–5 days on average for each process. NECVs mostly occur in late spring and early summer, and the longest time influenced by NECVs exceeds 19 days, with annual means of 9.9 days, 8.8 days, and 7.0 days in May, June, and July, respectively. The frequency of weak NECVs is about 1.2 times that of strong NECVs. Strong NCVs in late spring and early autumn as well as weak MCVs in summer are with high-frequency occurrences. It is found that when NCVs occur in late spring and early autumn, the upper-level westerly jets are relatively stronger, thus strengthening the divergence in the upper troposphere and the vortex circulation. The circulation fields in upper and lower levels cooperate with the strong jets, promoting the continuous development and maintenance of the cold vortices. Apart from the jets and circulation, the lower central potential height combined with the obvious cold-core and stronger ascending motions favor the NCV’s development. In addition, the dry intrusion has a strong promotion due to the stronger lower-level cold advection and downward intrusion of high potential vorticity. However, when MCVs occur in summer, things are just the opposite.
      PubDate: Wed, 14 Apr 2021 06:50:01 +000
  • The Impact of Tropical Cyclones in Premonsoonal Season on Local Convection
           over the Al-Hajar Mountains in Oman during 2007–2018

    • Abstract: The tropical cyclones (TCs) and convective storms have a significant impact on triggering widespread flooding in vulnerable areas. However, it is not clear whether the TCs stimulate the convective precipitation over the Al-Hajar Mountains in Oman or suppress it although it had been shown in many studies that TCs suppress the local convection development. This study aims to test the applicability of the hypothesis that the TCs suppress the convection over mountainous to the Al-Hajar Mountains. In order to test the hypothesis of tropical cyclones’ impact on local convection development over the Al-Hajar Mountains, this study considers three different cases during the premonsoon season between 2007 and 2018. The results revealed that weak local convection is reported over the Al-Hajar Mountains during the presence of the cyclones in the Arabian Sea and during the period of their direct impacts. The rainfall in these cases was mainly from stratiform clouds. Therefore, the impact of TCs on the convective suppression over the mountains is applicable to the Al-Hajar Mountains. This study will provide decision-makers and policy creators with knowledge as to whether the Al-Hajar Mountains are susceptible and vulnerable to the risk of torrential downpour, flash flooding, and thunderstorms as what is believed to be.
      PubDate: Mon, 12 Apr 2021 10:05:01 +000
  • Effects of Location-Specific Meteorological Factors on COVID-19 Daily
           Infection in a Tropical Climate: A Case of Kuala Lumpur, Malaysia

    • Abstract: Insufficient information on the novel coronavirus (COVID-19) has made it more difficult for the world to tackle its continuous implosion. Meteorological and environmental factors, in both laboratory and epidemiological studies, have been reported to affect the survival and transmission of the virus. In this study, the possible effects of location-specific meteorological parameters in a tropical climate on new daily COVID-19 infection (NDI) are investigated in Kuala Lumpur from 14 March 2020 to 31 August 2020. A generalized additive model (GAM) was imposed on ambient temperature (T) and absolute humidity (AH) to explore their nonlinear relationship with NDI. Piecewise linear regression was then used to further discern the relationships below and above the threshold values of both T and AH. The relationship between T and NDI, which was linear and statistically significant for T > 29.7°C, showed that each unit rise in temperature increases NDI by about 3.210% (CI: 1.372–7.976). AH had a more pronounced linear association with NDI for AH ≤ 22.6 g/m3 but tended to flatten the exposure-response curve above this value. A 1 g/m3 increase in AH increases NDI by 3.807% (CI: 2.064–5.732). Generally, the results indicated a positive association between T and NDI, particularly above 29.7°C, while the association with AH showed a stronger positive relationship below 22.6 g/m3. The implication of this is that COVID-19 could not be suppressed on account of warmer weather as such public health interventions remain imperative.
      PubDate: Sat, 10 Apr 2021 07:05:01 +000
  • Spatiotemporal Variations of Drought in the Arid Region of Northwestern
           China during 1950–2012

    • Abstract: There are water resource shortages and frequent drought disasters in the arid region of northwestern China (ARNC). The purpose of this study is to understand the spatiotemporal variations of the droughts in this region and to further estimate future changes. Multiple drought indexes such as the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), and the self-calibrated Palmer drought severity index (SC-PDSI) are used to investigate the temporal and spatial characteristics of the ARNC drought from 1950 to 2012. Our results indicate the following: (1) The drought indexes exhibit significant increasing trends, and the highest drought frequency occurred in the 1960s, followed by a decreasing trend during the next few decades. All four seasons exhibit a wet trend, with a higher drought frequency in summer than in the other seasons. (2) The changes of the drought indexes in the ARNC also exhibit distinct spatial variations, with a wet trend in the subregions of North Xinjiang (NXJ), the Tianshan Mountains (TS), South Xinjiang (SXJ), and the Qilian Mountains (QL), but with a dry trend in the subregions of the Hexi Corridor (HX) and the western part of Inner Mongolia (WIM). (3) There was a major climate variability in the ARNC that occurred in the 1980s, and there were dry and wet climate oscillation periods of 8a, 17a, and >20a.
      PubDate: Mon, 05 Apr 2021 06:20:02 +000
  • Analysis of the Response of Urban Water Consumption to Climatic Variables:
           Case Study of Khorramabad City in Iran

    • Abstract: Iran is located in a dry climate belt. Such conditions have made the supply of urban water resources one of the most fundamental management challenges. The amount of water consumed in a city is affected by the weather conditions greatly such that as the weather changes, the amount of water consumed changes as well. In this study, several models including zero-order Pearson’s correlation coefficient, first-order Pearson’s correlation, generalized additive model (GAM), generalized linear model (GLM), support vector machine (SVM-Nu), and simplex optimization algorithm were used in order to identify linear/nonlinear reactions of monthly water consumption to the individual and combined associations of meteorological variables (temperature, air pressure, and relative humidity) in Khorramabad city. Zero-order and first-order correlations showed that, by controlling the air temperature, the effect of pressure and relative humidity on changes in water consumption increase. On the other hand, both individual and combined GAM models showed the same result in the nonlinear response of water consumption to the changes in relative humidity and air pressure. The spline method also revealed that, by eliminating the effect of air temperature, the nonlinear reaction of water consumption to changes in pressure and relative humidity was increasing, and by eliminating the effects of the relative humidity and air pressure, the nonlinear reaction of water consumption to the air temperature was intensified. In general, by decreasing the air pressure and temperature, the amount of urban household water consumption decreases drastically. These conditions are generally provided by entering low-pressure systems.
      PubDate: Fri, 19 Mar 2021 06:05:02 +000
  • Observed Shear-Relative Rainfall Asymmetries Associated with Landfalling
           Tropical Cyclones

    • Abstract: This study examines the shear-relative rainfall spatial distribution of tropical cyclones (TCs) during landfall based on the 19-year (1998–2016) TRMM satellite 3B42 rainfall estimate dataset and investigates the role of upper-tropospheric troughs on the rainfall intensity and distribution after TCs make a landfall over the six basins of Atlantic (ATL), eastern and central Pacific (EPA), northwestern Pacific (NWP), northern Indian Ocean (NIO), southern Indian Ocean (SIO), and South Pacific (SPA). The results show that the wavenumber 1 perturbation can contribute ∼ 50% of the total perturbation energy of total TC rainfall. Wavenumber 1 rainfall asymmetry presents the downshear-left maxima in the deep-layer vertical wind shear between 200 and 850 hPa for all the six basins prior to making a landfall. In general, wavenumber 1 rainfall tends to decrease less if there is an interaction between TCs and upper-level troughs located at the upstream of TCs over land. The maximum TC rain rate distributions tend to be located at the downshear-left (downshear) quadrant under the high (low)-potential vorticity conditions.
      PubDate: Wed, 10 Mar 2021 12:05:00 +000
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