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  Subjects -> METEOROLOGY (Total: 112 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 198)
Nature Climate Change     Full-text available via subscription   (Followers: 133)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 80)
Atmospheric Environment     Hybrid Journal   (Followers: 73)
Atmospheric Research     Hybrid Journal   (Followers: 69)
Climatic Change     Open Access   (Followers: 64)
Journal of Climate     Hybrid Journal   (Followers: 54)
Bulletin of the American Meteorological Society     Open Access   (Followers: 51)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 48)
Climate Dynamics     Hybrid Journal   (Followers: 44)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 43)
Climate Policy     Hybrid Journal   (Followers: 42)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 37)
Atmospheric Science Letters     Open Access   (Followers: 36)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 35)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 34)
Monthly Weather Review     Hybrid Journal   (Followers: 34)
International Journal of Climatology     Hybrid Journal   (Followers: 31)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 31)
American Journal of Climate Change     Open Access   (Followers: 29)
Advances in Climate Change Research     Open Access   (Followers: 29)
Journal of Hydrology and Meteorology     Open Access   (Followers: 29)
Developments in Atmospheric Science     Full-text available via subscription   (Followers: 28)
Weather and Forecasting     Hybrid Journal   (Followers: 28)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 27)
Journal of Space Weather and Space Climate     Open Access   (Followers: 27)
Atmosphere     Open Access   (Followers: 26)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 26)
Space Weather     Full-text available via subscription   (Followers: 25)
Advances in Meteorology     Open Access   (Followers: 24)
Energy & Environment     Hybrid Journal   (Followers: 24)
Tellus A     Open Access   (Followers: 22)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 21)
International Journal of Atmospheric Sciences     Open Access   (Followers: 21)
Tellus B     Open Access   (Followers: 21)
Climate Change Economics     Hybrid Journal   (Followers: 20)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Weather     Hybrid Journal   (Followers: 19)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 18)
Global Meteorology     Open Access   (Followers: 17)
Weather and Climate Extremes     Open Access   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 15)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 14)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 13)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 11)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Climate Change Responses     Open Access   (Followers: 10)
Climate Resilience and Sustainability     Open Access   (Followers: 9)
Climate law     Hybrid Journal   (Followers: 8)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 7)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 7)
Climate Change Research Letters     Open Access   (Followers: 7)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 6)
Mathematics of Climate and Weather Forecasting     Open Access   (Followers: 6)
Climate Research     Hybrid Journal   (Followers: 6)
Aeolian Research     Hybrid Journal   (Followers: 6)
Current Climate Change Reports     Hybrid Journal   (Followers: 6)
Open Journal of Modern Hydrology     Open Access   (Followers: 6)
Climate     Open Access   (Followers: 6)
Change and Adaptation in Socio-Ecological Systems     Open Access   (Followers: 5)
Climate Risk Management     Open Access   (Followers: 5)
The Cryosphere (TC)     Open Access   (Followers: 5)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 5)
Climate of the Past (CP)     Open Access   (Followers: 5)
International Journal of Environment and Climate Change     Open Access   (Followers: 4)
Urban Climate     Hybrid Journal   (Followers: 4)
Environmental and Climate Technologies     Open Access   (Followers: 4)
Carbon Balance and Management     Open Access   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
The Cryosphere Discussions (TCD)     Open Access   (Followers: 4)
Weatherwise     Hybrid Journal   (Followers: 4)
Meteorological Applications     Hybrid Journal   (Followers: 4)
Climate Services     Open Access   (Followers: 3)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 3)
Atmósfera     Open Access   (Followers: 3)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 3)
Journal of Climatology     Open Access   (Followers: 3)
Ciencia, Ambiente y Clima     Open Access   (Followers: 3)
Frontiers in Climate     Open Access   (Followers: 3)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 3)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3)
Atmospheric Environment : X     Open Access   (Followers: 3)
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Journal of Weather Modification     Full-text available via subscription   (Followers: 2)
Open Atmospheric Science Journal     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Journal of Climate Change     Full-text available via subscription   (Followers: 2)
Climate and Energy     Full-text available via subscription   (Followers: 2)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
Climate Summary of South Africa     Full-text available via subscription   (Followers: 2)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
气候与环境研究     Full-text available via subscription   (Followers: 1)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 1)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
International Journal of Biometeorology     Hybrid Journal   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Mediterranean Marine Science     Open Access   (Followers: 1)
Large Marine Ecosystems     Full-text available via subscription   (Followers: 1)
Weather and Climate Dynamics     Open Access  
Journal of Agricultural Meteorology     Open Access  
Nīvār     Open Access  
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  
Earth Perspectives - Transdisciplinarity Enabled     Open Access  
Climate of the Past Discussions (CPD)     Open Access  
Revista Brasileira de Meteorologia     Open Access  
Studia Geophysica et Geodaetica     Hybrid Journal  

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Advances in Meteorology
Journal Prestige (SJR): 0.48
Citation Impact (citeScore): 1
Number of Followers: 24  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-9309 - ISSN (Online) 1687-9317
Published by Hindawi Homepage  [343 journals]
  • 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
  • Impacts of Sea Surface Temperature and Atmospheric Teleconnection Patterns
           in the Northern Mid-Latitudes on Winter Extremely Cold Events in North

    • Abstract: The frequency distribution of winter extreme cold events (ECEs) in North China and the influences of mid-latitude sea surface temperature anomalies (SSTAs) in the Northern Hemisphere are studied. The results show that (1) the frequency of single station ECEs (SSECEs) in winter increases from southeast to northwest, with a decrease before 2008 and then a significant increase. This trend abrupt change occurs in late winter. (2) When the SST in the North Pacific shows an “El-Niño-like” anomaly in winter, it triggers the negative Arctic Oscillation (−AO), positive Pacific North America (+PNA), and positive Eurasia Pacific (+EUP) atmospheric teleconnection patterns in the mid-lower troposphere. As a result, the ridge to south of Lake Baikal becomes stronger. Meanwhile, SST in the North Atlantic shows a “reversed C” negative anomaly with North Atlantic Oscillation (+NAO), (+PNA)-like and (+EUP)-like patterns, and the ridge to southwest of Lake Baikal becomes stronger. Furthermore, both cause the Siberian High to become weaker in the north and stronger in the south. With the weaker East Asia subtropical jet and stronger East Asia winter monsoon, these factors lead to a significant increase of SSECE frequency in North China. (3) When the SSTA shows an “El Niño-like” developing pattern from summer to autumn in the North Pacific, the winter SSECE frequency will be higher. (4) The purported mechanism between the mid-latitude SSTA and the winter SSECE frequency in North China is the following: the SSTA in the North Pacific in summer and autumn excites atmospheric teleconnection wave trains, and the Atlantic stores these anomaly signals. In winter, the interaction between the SSTAs in the North Pacific and the North Atlantic enhances the Eurasian teleconnection wave train. With the upstream fluctuation energy dispersing downstream, the wave train centers move eastward with the season, resulting in an increase in the frequency of the SSECEs.
      PubDate: Tue, 09 Mar 2021 09:20:01 +000
  • Statistical Characteristics of Raindrop Size Distribution during Rainy
           Seasons in Northwest China

    • Abstract: Raindrop size distribution (DSD) is of great significance for understanding the microphysical process of rainfall and the quantitative precipitation estimation (QPE). However, in the past, there was a lack of relevant research on Xinjiang in the arid region of northwest China. In this study, the rainy season data collected by the disdrometer in the Yining area of Xinjiang were used for more than two years, and the characteristics of DSDs for all samples, for two rain types (convective and stratiform), and for six different rain rates were studied. The results showed that nearly 70% of the total samples had a rainfall rate of less than 1 mm·h−1, the convective rain was neither continental nor maritime, and there was a clear boundary between convective rain and stratiform rain in terms of the scattergram of the standardized intercept parameter () versus the mass-weighted average diameter (). When the raindrop diameter was less than 0.7 mm, DSDs of the two rainfalls basically coincided, while when the raindrop diameter was greater than 0.7 mm, DSDs of convective rainfall were located above the stratiform rain. As the rainfall rate increased, increased, while first increased and then decreased. In addition, we deduced the (radar reflectivity-rain rate) relationship and relationship (shape parameter-slope parameter of the gamma DSDs) suitable for the Yining area. These conclusions are conducive to strengthening the understanding of rainfall microphysical processes in arid regions and improving the ability of QPE in arid regions.
      PubDate: Mon, 08 Mar 2021 08:20:01 +000
  • Assimilation of MWHS-2/FY-3C 183 GHz Channels Using a Dynamic Emissivity
           Retrieval and Its Impacts on Precipitation Forecasts: A Southwest Vortex

    • Abstract: The dynamic emissivity retrieved from window channels of the microwave humidity sounder II (MWHS-2) onboard the China Meteorological Administration’s FengYun (FY)-3C polar orbiting satellite can provide more realistic emissivity over lands and potentially improve the numerical weather prediction (NWP) forecasts. However, whether the assimilation with the dynamic emissivity works for the precipitation forecasts over the complex geography is less investigated. In this paper, a typical precipitating case generated by the Southwest Vortex is selected and the Weather Research and Forecasting data assimilation (WRFDA) system is applied to examine the impacts of assimilating MWHS-2/FY-3C with the uses of the emissivity atlas and the dynamic emissivity on the forecasts. The results indicate that the use of the dynamic emissivity retrieved from the 89 GHz channel of MWHS-2/FY-3C apparently increases the used data number for assimilation and does improve the initial fields and the 24-hour forecasts (from 0000 UTC 24 June 2016 to 0000 UTC 25 June 2016) of precipitation distribution and intensity except for the rainfall over 100 mm. But these positive impacts are not evidently better than those with the emissivity atlas. In general, these results still suggest that the future use of the dynamic emissivity in the assimilation over the complex terrain is promising.
      PubDate: Sat, 27 Feb 2021 13:35:01 +000
  • Evaluation of Zenith Tropospheric Delay Derived from Ray-Traced VMF3
           Product over the West African Region Using GNSS Observations

    • Abstract: The growing demand for Global Navigation Satellite System (GNSS) technology has necessitated the establishment of a vast and ever-growing network of International GNSS Service (IGS) tracking stations worldwide. The IGS provides highly accurate and highly reliable daily time-series Zenith Tropospheric Delay (ZTD) products using data from the member sites towards the use of GNSS for precise geodetic, climatological, and meteorological applications. However, if for reasons like poor internet connectivity, equipment failure, and power outages, the IGS station is inaccessible or malfunctioning, and gaps are created in the data archive resulting in degrading the quality of the ZTD and precipitable water vapour (PWV) estimation. To address this challenge as a means of providing an alternative data source to improve the continuous availability of ZTD data and as a backup data in the event that the IGS site data are missing or unavailable in West Africa, this paper compares the sitewise operational Vienna Mapping Functions 3 (VMF3) ZTD product with the IGS final ZTD product over five IGS stations in West Africa. Eight different statistical evaluation metrics, such as the mean bias (MB), mean absolute error (MAE), root mean squared error (RMSE), Pearson correlation coefficient (r), coefficient of determination (r2), refined index of agreement (IAr), Nash–Sutcliffe coefficient of efficiency (NSE), and the fraction of prediction within a factor of two (FAC2), are employed to determine the degree of agreement between the VMF3 and IGS tropospheric products. The results show that the VMF3-ZTD product performed excellently and matches very well with the IGS final ZTD product with an average MB, MAE, RMSE, r, r2, NSE, IAr, and FAC2 of 0.38 cm, 0.87 cm, 1.11 cm, 0.988, 0.976, 0.967, 0.992, and 1.00 (100%), respectively. This result is an indication that the VMF3-ZTD product is accurate enough to be used as an alternative source of ZTD data to augment the IGS final ZTD product for positioning and meteorological applications in West Africa.
      PubDate: Sat, 27 Feb 2021 13:20:01 +000
  • Evaluating the Performance of a WRF Physics Ensemble in Simulating
           Rainfall over Lao PDR during Wet and Dry Seasons

    • Abstract: Dynamical downscaling of General Circulation Model (GCM) data for any region has been made possible due to a set of physics options and model dynamics within the Weather Research and Forecasting (WRF) model. This study evaluated the performance of an ensemble of physics options in simulating rainfall during wet and dry seasons of Lao PDR. The model evaluation criteria focused on identifying the optimum physics options for a range of scenarios. No single combination of physics options performed well in all scenarios reflecting the importance of using different parameterizations according to the geographic location and the intended application of the results. For the dry season, none of the ensemble members performed satisfactorily for the southern region of Lao PDR, while all the ensemble members performed well for the northern and central regions. While almost all the WRF simulations overestimated the rainfall during the wet season, BMJ for cumulus physics performed better in the northern and central regions, and KF performed better in the south region. The YSU scheme performed best as the planetary boundary layer for both wet and dry seasons, while WSM5 for the wet season and Lin for the dry season gave the best model performance as the microphysics option.
      PubDate: Thu, 11 Feb 2021 13:05:01 +000
  • Determination of the Influence of Fuel Switching Regulation on the Sulfur
           Dioxide Content of Air in a Port Area Using DID Model

    • Abstract: Since January 1, 2018, ships berthed at all ports of the three designated emission control areas (ECAs) in China are required to use fuel with sulfur content not exceeding 0.5% (m/m), excluding one hour postarrival and one hour predeparture. To understand changes in SO2 due to this policy, two observation stations were established on Waigaoqiao Dock in the Yangtze River estuary. Three data types were collected from March 2018 to May 2018, namely, wind speed and direction, SO2 concentration, and ships’ arrival and departure times. The statistics indicate that the wind direction changed little during the observation period and SO2 concentration was below 5 µg/m3 77.47% of the time. Meanwhile, ships’ arrival and departure at the dock had a distinct influence on overall SO2 distribution, including occurrence of concentrations ≥5 µg/m3. The three types of data were divided into six groups and a difference-in-difference model was used for analysis. The result shows that SO2 concentration increases due to the use of high-sulfur fuel and is especially significant when the wind is southwesterly. Furthermore, there was a positive correlation between increases in SO2 concentrations over 5 µg/m3 and the number of ships arriving or departing from the port. This study reports the positive impact of fuel switching on air quality and can be used to evaluate adherence to the ECA policy.
      PubDate: Tue, 09 Feb 2021 14:20:02 +000
  • Spatiotemporal Rainfall Distribution of Soan River Basin, Pothwar Region,

    • Abstract: This study evaluates the spatiotemporal rainfall variability over the semimountainous Soan River Basin (SRB) of sub-Himalayan Pothwar region, Pakistan. The temporal rainfall trend analysis of sixteen rain gauges was performed on annual basis with long-term (1981–2016) data. The results depicted that there is substantial year-to-year and season-to-season variability in rainfall patterns, and rainfall patterns are generally erratic in nature. The results highlight that most of the highland rainfall stations showed decreasing trends on annual basis. The central and lowland stations of the study area recorded an increasing trend of rainfall except for Talagang station. The average annual rainfall of the study area ranges between 492 mm and 1710 mm in lowland and high-altitude areas, respectively. Of the whole year’s rainfall, about 70 to 75% fall during the monsoon season. The rainfall spatial distribution maps obtained using the inverse distance weighting (IDW) method, through the GIS software, revealed the major rainfall range within the study area. There is a lack of water during postmonsoon months (November–February) and great differences in rainfall amounts between the mountainous areas and the lowlands. There is a need for the rational management of mountainous areas using mini and check dams to increase water production and stream regulation for lowland areas water availability. The spatiotemporal rainfall variability is crucial for better water resource management schemes in the study area of Pothwar region, Pakistan.
      PubDate: Mon, 08 Feb 2021 08:35:01 +000
  • Investigation on the Impacts of COVID-19 Lockdown and Influencing Factors
           on Air Quality in Greater Bangkok, Thailand

    • Abstract: With the outbreak of the COVID-19 pandemic around the world, many countries announced lockdown measures, including Thailand. Several scientific studies have reported on improvements in air quality due to the impact of these COVID-19 lockdowns. This study aims to investigate the effects of the COVID-19 lockdown and its driving influencing factors on air pollution in Greater Bangkok, Thailand, using in situ measurements. Overall, PM2.5, PM10, O3, and CO concentrations presented a significant decreasing trend during the COVID-19 outbreak year based on three periods: the Before Lockdown, Lockdown, and After Lockdown periods, for PM2.5: −0.7%, −15.8%, and −20.7%; PM10: −4.1%, −31.7%, and −6.1%; and O3: −0.3%, −7.1%, and −4.7%, respectively, compared to the same periods in 2019. CO concentrations, especially which had increased by 14.7% Before Lockdown, decreased by −8.0% and −23.6% during the Lockdown and After Lockdown periods, respectively. Meanwhile, SO2 increased by 54.0%, 41.5%, and 84.6%, and NO2 increased by 20.1%, 3.2%, and 26.6%, respectively, for the Before Lockdown, Lockdown, and After Lockdown periods. PCA indicated a significant combination effect of atmospheric mechanisms that were strongly linked to emission sources such as traffic and biomass burning. It has been demonstrated that the COVID-19 lockdown did pause some of these anthropogenic emissions, i.e., traffic and commercial and industrial activities, but not all of them. Even low traffic emissions, on their own, did not cause an absolute reduction in air pollution since there are several primary emission sources that dominate the air quality over Greater Bangkok. Finally, these findings highlight the impact of COVID-19 lockdown measures not only on air pollution levels but on their effects on air pollution characteristics, as well.
      PubDate: Thu, 04 Feb 2021 15:05:01 +000
  • Vegetation Change and Its Response to Climate Change in Yunnan Province,

    • Abstract: The impact of global climate change on vegetation has become increasingly prominent over the past several decades. Understanding vegetation change and its response to climate can provide fundamental information for environmental resource management. In recent years, the arid climate and fragile ecosystem have led to great changes in vegetation in Yunnan Province, so it is very important to further study the relationship between vegetation and climate. In this study, we explored the temporal changes of normalized difference vegetation index (NDVI) in different seasons based on MOD13Q1 NDVI by the maximum value composite and then analyzed spatial distribution characteristics of vegetation using Sen’s tendency estimation, Mann–Kendall significance test, and coefficient of variation model (CV) combined with terrain factors. Finally, the concurrent and lagged effects of NDVI on climate factors in different seasons and months were discussed using the Pearson correlation coefficient. The results indicate that (1) the temporal variation of the NDVI showed that the NDVI values of different vegetation types increased at different rates, especially in growing season, spring, and autumn; (2) for spatial patterns, the NDVI, CV, and NDVI trends had strong spatial heterogeneity owning to the influence of altitudes, slopes, and aspects; and (3) the concurrent effect of vegetation on climate change indicates that the positive effect of temperature on NDVI was mainly in growing season and autumn, whereas spring NDVI was mainly influenced by precipitation. In addition, the lag effect analysis results revealed that spring precipitation has a definite inhibition effect on summer and autumn vegetation, but spring and summer temperature can promote the growth of vegetation. Meanwhile, the precipitation in the late growing season has a lag effect of 1-2 months on vegetation growth, and air temperature has a lag effect of 1 month in the middle of the growing season. Based on the above results, this study provided valuable information for ecosystem degradation and ecological environment protection in the Yunnan Province.
      PubDate: Thu, 04 Feb 2021 08:20:00 +000
  • Impact of Large-Scale Climate Indices on Meteorological Drought of Coastal

    • Abstract: The devastating effects of drought on agriculture, water resources, and other socioeconomic activities have severe consequences on food security and water resource management. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. In this study, meteorological droughts over six coastal synoptic stations were investigated using three-month Standardized Precipitation Index (SPI). The dry seasons of November-December-January (NDJ), December-January-February (DJF), and January-February-March (JFM) were the focal seasons for the study. Trends of dry seasons SPIs were evaluated using seasonal Mann–Kendall test. The relationship between drought SPI and ocean-atmosphere climate indices and their predictive ability were assessed using Pearson correlation and Akaike Information Criterion (AIC) stepwise regression method to select best climate indices at lagged timestep that fit the SPI. The SPI exhibited moderate to severe drought during the dry seasons. Accra exhibited a significant increasing SPI trend in JFM, NDJ, and DJF seasons. Besides, Saltpond during DJF, Tema, and Axim in NDJ season showed significant increasing trend of SPI. In recent years, SPIs in dry seasons are increasing, an indication of weak drought intensity, and the catchment areas are becoming wetter in the traditional dry seasons. Direct (inverse) relationship was established between dry seasons SPIs and Atlantic (equatorial Pacific) ocean's climate indices. The significant climate indices modulating drought SPIs at different time lags are a combination of either Nino 3.4, Nino 4, Nino 3, Nino 1 + 2, TNA, TSA, AMM, or AMO for a given station. The AIC stepwise regression model explained up to 48% of the variance in the drought SPI and indicates Nino 3.4, Nino 4, Nino 3, Nino 1 + 2, TNA, TSA, AMM, and AMO have great potential for seasonal drought prediction over Coastal Ghana.
      PubDate: Wed, 03 Feb 2021 14:05:00 +000
  • Development and Evaluation of a Hydrometeorological Forecasting System

    • Abstract: In this study, an experimental hydrometeorological forecasting system was developed based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) model. The system downloads global real-time ocean, atmosphere, and wave forcing data, producing regional forecasts every day. A coastal area in South China, encompassing Hainan Island, Leizhou Peninsula, and surrounding sea areas, was chosen as the study domain. A series of 72-hour forecasting simulations were conducted in the area, lasting from July 27 to August 31, 2019. The forecasts throughout August were chosen for evaluation with station observations, along with two sets of reanalysis data, ERA5 and CLDAS. The evaluation results revealed that the COAWST model had high potential for routine forecasting operations. The 24 h forecasts, with a lead time of 24 hours, had high accuracy, while the 48 h and 72 h forecasts did not differ greatly in terms of performance. The distributions of bias between forecast and reanalysis data showed obvious differences between land and sea, with more forecasted precipitation and lower temperatures in land grids than in sea grids. In most cases, the forecasts were closer to ERA5 in terms of means and other statistical measures. The forecasts enlarged the land-sea differences of temperature when compared with ERA5 and strengthened summer monsoon with more moisture transported to land areas. Resulting from that, a forecasted bias of lower surface pressure, higher air humidity, stronger south wind, and so forth was also detected over the domain but at low values.
      PubDate: Tue, 19 Jan 2021 07:05:01 +000
  • Numerical Simulation of Near-Surface Wind during a Severe Wind Event in a
           Complex Terrain by Multisource Data Assimilation and Dynamic Downscaling

    • Abstract: Accurate forecast and simulation of near-surface wind is a great challenge for numerical weather prediction models due to the significant transient and intermittent nature of near-surface wind. Based on the analyses of the impact of assimilating in situ and Advanced Tiros Operational Vertical Sounder (ATOVS) satellite radiance data on the simulation of near-surface wind during a severe wind event, using the new generation mesoscale Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system, the dynamic downscaling of near-surface wind is further investigated by coupling the microscale California Meteorological (CALMET) model with the WRF and its 3DVAR system. Results indicate that assimilating in situ and ATOVS radiance observations strengthens the airflow across the Alataw valley and triggers the downward transport of momentum from the upper atmosphere in the downstream area of the valley in the initial conditions, thus improving near-surface wind simulations. Further investigations indicate that the CALMET model provides more refined microtopographic structures than the WRF model in the vicinity of the wind towers. Although using the CALMET model achieves the best simulation of near-surface wind through dynamic downscaling of the output from the WRF and its 3DVAR assimilation, the simulation improvements of near-surface wind speed are mainly within 1 m s−1. Specifically, the mean improvement proportions of near-surface wind speed are 64.8% for the whole simulation period, 58.7% for the severe wind period, 68.3% for the severe wind decay period, and 75.4% for the weak wind period. The observed near-surface wind directions in the weak wind conditions are better simulated in the coupled model with CALMET downscaling than in the WRF and its 3DVAR system. It is concluded that the simulation improvements of CALMET downscaling are distinct when near-surface winds are weak, and the downscaling effects are mainly manifested in the simulation of near-surface wind directions.
      PubDate: Wed, 30 Dec 2020 12:50:01 +000
  • Diurnal Variation of Seasonal Precipitation over the CONUS: A Comparison
           of Gauge Observations with TRMM Data

    • Abstract: Diurnal variation of precipitation is a fundamental periodic signal of local climate. Comprehensive study of diurnal variation of precipitation is helpful in studying the formation of local climate and validating satellite precipitation products. In this study, a comparison is drawn between precipitation gauge observations and Tropical Rainfall Measuring Mission (TRMM) 3B42 data on diurnal variation of precipitation. First, using the K-means clustering algorithm, stations with gauge observations and pixels with TRMM data are divided into different groups according to the diurnal variation of precipitation, respectively. In each group, the stations have similar diurnal variation of precipitation. Then maps of diurnal variation of precipitation for gauge observations and TRMM data are obtained. According to these maps, the diurnal variation of precipitation over the contiguous United States (CONUS) presents seasonal variability in both gauge observations and TRMM data. In addition, the diurnal variation of precipitation shows clustered features in space. However, the spatial patterns of the obtained maps do not match, and the TRMM satellite data perform poorly in capturing the hourly precipitation event. Finally, the possible mechanism behind the prevailing nocturnal precipitation over the middle of the CONUS is discussed, with the prevailing nocturnal precipitation judged likely to be strongly related to the mountain-plains solenoid (MPS) circulation.
      PubDate: Thu, 24 Dec 2020 16:35:00 +000
  • Corrigendum to “Projected Changes in Precipitation Extremes over Shaanxi
           Province, China, in the 21st Century”

    • PubDate: Mon, 21 Dec 2020 13:35:01 +000
  • Application of Multiple Detection Data in the Analysis of Snowstorm
           Processes in Xinjiang during the Central Asia Extreme Precipitation
           Observation Test (CAEPOT)

    • Abstract: At present, there is insufficient research on the refinement of the vertical structure of winter snowstorm systems in arid areas, and, compared with the central and eastern China, the observation sites in arid areas of northwestern China are scarce. To deepen the understanding of dynamics and microphysical processes and improve the level of forecasting and warning of snowstorms in northwestern China, the Institute of Desert Meteorology, China Meteorological Administration, Urumqi, carried out the Central Asia Extreme Precipitation Observation Test (CAEPOT) in Yili, Xinjiang, a typical arid region in China in February 2020. This paper uses multiple fine detection datasets obtained from the CAEPOT, including radar wind profiler, ground-based microwave radiometer, and millimeter-wave cloud radar to analyze macroscopic characteristics and microphysical changes of snowstorm system in Xinjiang. Studies have shown that the low trough with sufficient moisture, heat, power conditions, and weakening banded cloud system, which moved eastward from the Aral Sea to the west of Xinjiang during the snowstorm, were the key influencing system of this snowstorm. Before the snowstorm, the vertical shear of the horizontal wind field was severe, which aggravated the instability of the atmosphere, and there was upward motion in the lower atmosphere. A variety of physical quantities related to moisture showed a tendency to increase at the lower level and could be used as an early warning signal for snowstorm about 8 hours in advance, and the cloud and snow particles observed by millimeter-wave cloud radar were simultaneously developing upward and downward from 4 km, providing snowstorm warning 12 hours in advance. During the snowstorm, the horizontal wind speed and vertical speed were obviously enhanced, and the physical quantities related to moisture further increased, and, with the blocking and uplifting of the Tianshan Mountains, the snowstorm increased. The particles collided and grew while falling, resulting in a decrease in particle concentration and an increase in particle radius from high altitude to the ground, eventually resulting in near-ground reflectivity factor up to 30 dBz. In addition, reflectivity factor, physical quantities related to moisture, wind field, particle concentration, and particle radius all had a good correspondence with the beginning, end, and intensity of snowstorm, so when the physical quantities mentioned above weakened and stopped, snowstorm also weakened and stopped. In a word, this research is an important and meaningful work that provides more backgrounds and references for the forecast and warning of snowstorm in northwestern China.
      PubDate: Mon, 21 Dec 2020 07:35:01 +000
  • Mountain Waves Analysis in the Vicinity of the Madrid-Barajas Airport
           Using the WRF Model

    • Abstract: Turbulence and aircraft icing associated with mountain waves are weather phenomena potentially affecting aviation safety. In this paper, these weather phenomena are analysed in the vicinity of the Adolfo Suárez Madrid-Barajas Airport (Spain). Mountain waves are formed in this area due to the proximity of the Guadarrama mountain range. Twenty different weather research and forecasting (WRF) model configurations are evaluated in an initial analysis. This shows the incompetence of some experiments to capture the phenomenon. The two experiments showing the best results are used to simulate thirteen episodes with observed mountain waves. Simulated pseudosatellite images are validated using satellite observations, and an analysis is performed through several skill scores applied to brightness temperature. Few differences are found among the different skill scores. Nevertheless, the Thompson microphysics scheme combined with the Yonsei university PBL scheme shows the best results. The simulations produced by this scheme are used to evaluate the characteristic variables of the mountain wave episodes at windward and leeward and over the mountain. The results show that north-northwest wind directions, moderate wind velocities, and neutral or slightly stable conditions are the main features for the episodes evaluated. In addition, a case study is analysed to evidence the WRF ability to properly detect turbulence and icing associated with mountain waves, even when there is no visual evidence available.
      PubDate: Fri, 18 Dec 2020 15:50:01 +000
  • Spatial Distribution and Temporal Trends in the Daily Precipitation
           Concentration across the Yarlung Tsangpo River Basin: Eastern Himalaya of

    • Abstract: Understanding the temporal inequality in precipitation is of great importance for water resource management, environmental risk management, and ecological conservation. This study investigated the spatial patterns and trends of the daily precipitation concentration over the Yarlung Tsangpo River Basin using the concentration index (CI) and the Lorentz asymmetric coefficient (LAC). A Mann–Kendall test and Hurst’s rescaled range analysis were used to detect the change in CI trends. The CI ranged from 0.58 to 0.65, suggesting that a quarter of the rainiest days contributed approximately 69–78% of the total precipitation. The LAC analysis indicated that the nonuniform distribution of precipitation was mainly attributed to a large proportion of days with light rainfall. Compared with that of the central region, the daily precipitation in the western and eastern regions was more irregular. At a seasonal scale, the dry season had a less homogeneous spatial distribution of CI compared to that of the wet season. Most areas exhibited no significant trends in CI from 1970 to 2017. A quarter of the stations presented a significant downward trend in CI, which were primarily found in the central and northern regions. In addition, the future trends of CI in most areas mostly agree with those of the current state; however, the majority of stations exhibited an uneven precipitation distribution in the dry season.
      PubDate: Tue, 15 Dec 2020 07:50:01 +000
  • Evaluation and Analysis of Soil Temperature Data over Poyang Lake Basin,

    • Abstract: Soil temperature reflects the impact of local factors, such as the vegetation, soil, and atmosphere of a region. Therefore, it is important to understand the regional variation of soil temperature. However, given the lack of observations with adequate spatial and/or temporal coverage, it is often difficult to use observational data to study the regional variation. Based on the observational data from Nanchang and Ganzhou stations and ERA-Interim/Land reanalysis data, this study analyzed the spatiotemporal distribution characteristics of soil temperature over Poyang Lake Basin. Four soil depths were examined, 0–7, 7–28, 28–100, and 100–289 cm, recorded as ST1, ST2, ST3, and ST4, respectively. The results showed close correlations between observation data and reanalysis data at different depths. Reanalysis data could reproduce the main spatiotemporal distributions of soil temperature over the Poyang Lake Basin but generally underestimated their magnitudes. Temporally, there was a clear warming trend in the basin. Seasonally, the temperature increase was the most rapid in spring and the slowest in summer, except for ST4, which increased the fastest in spring and the slowest in winter. The temperature increase was faster for ST1 than the other depths. The warming trend was almost the same for ST2, ST3, and ST4. An abrupt change of annual soil temperature at all depths occurred in 1997, and annual soil temperatures at all depths were abnormally low in 1984. Spatially, annual soil temperature decreased with latitude, except for the summer ST1. Because of the high temperature and precipitation in summer, the ST1 values were higher around the lake and the river. The climatic trend of soil temperature generally increased from south to north, which was opposite to the distribution of soil temperature. These findings provide a basis for understanding and assessing the variation of soil temperature in the Poyang Lake Basin.
      PubDate: Tue, 08 Dec 2020 14:35:01 +000
  • Quantifying the Location Error of Precipitation Nowcasts

    • Abstract: In precipitation nowcasting, it is common to track the motion of precipitation in a sequence of weather radar images and to extrapolate this motion into the future. The total error of such a prediction consists of an error in the predicted location of a precipitation feature and an error in the change of precipitation intensity over lead time. So far, verification measures did not allow isolating the extent of location errors, making it difficult to specifically improve nowcast models with regard to location prediction. In this paper, we introduce a framework to directly quantify the location error. To that end, we detect and track scale-invariant precipitation features (corners) in radar images. We then consider these observed tracks as the true reference in order to evaluate the performance (or, inversely, the error) of any model that aims to predict the future location of a precipitation feature. Hence, the location error of a forecast at any lead time Δt ahead of the forecast time t corresponds to the Euclidean distance between the observed and the predicted feature locations at t + Δt. Based on this framework, we carried out a benchmarking case study using one year worth of weather radar composites of the German Weather Service. We evaluated the performance of four extrapolation models, two of which are based on the linear extrapolation of corner motion from t − 1 to t (LK-Lin1) and t − 4 to t (LK-Lin4) and the other two are based on the Dense Inverse Search (DIS) method: motion vectors obtained from DIS are used to predict feature locations by linear (DIS-Lin1) and Semi-Lagrangian extrapolation (DIS-Rot1). Of those four models, DIS-Lin1 and LK-Lin4 turned out to be the most skillful with regard to the prediction of feature location, while we also found that the model skill dramatically depends on the sinuosity of the observed tracks. The dataset of 376,125 detected feature tracks in 2016 is openly available to foster the improvement of location prediction in extrapolation-based nowcasting models.
      PubDate: Thu, 03 Dec 2020 08:35:01 +000
  • Simulating Heavy Meiyu Rainfall: A Note on the Choice of the Model
           Microphysics Scheme

    • Abstract: Better simulations and predictions of heavy rainfall associated with Meiyu fronts are critical for flood management in the Yangtze River Valley, China. This work systematically evaluates and compares the performances of three microphysics schemes in Weather Research and Forecasting (WRF) Model with regard to simulating properties of a classic Meiyu rainstorm in central China which occurred during a 30-hour period in July 2016, including spatial distribution, rain rate PDF, and lifecycle behavior of local rainfall. Model simulations are validated using both in situ and remote sensing observations. It is found that all three schemes capture the overall spatial distribution of precipitation and the average rainfall intensity changes more rapidly with time in the simulation than in the observation. Further insights are gained through an examination of the budget terms of raindrop and ice-phase hydrometeors in the model. Accretion of cloud droplets by raindrops and melting of ice-phase hydrometeors are the major source of rainwater. Bergeron and riming processes are found to play a prevailing role in the growth of ice-phase hydrometeors in Meiyu rainfall. Large differences in the parameterization of riming process in different schemes lead to significant differences in the simulated growth of ice-phase hydrometeors.
      PubDate: Sun, 29 Nov 2020 09:50:01 +000
  • Bayesian Spatial and Trend Analysis on Ozone Extreme Data in South Korea:

    • Abstract: Background. Extreme events like flooding, extreme temperature, and ozone depletion are happening in every corner of the world. Thus, the need to model such rare events having enormous damage has been getting priorities in most countries of the world. Methods. The dataset contains the ozone data from 29 representative air monitoring sites in South Korea collected from 1991 to 2015. Spatial generalized extreme value (GEV) using maximum likelihood estimation (MLE) and two max-stable and Bayesian kriging models are the statistical models used for analysis. Moreover, predictive performances of these statistical models are compared using measures like root-mean-squared error (RMSE), mean absolute error (MAE), relative bias (rBIAS), and relative mean separation (rMSEP) have been utilized. Results. From the time plot of ozone data, extreme ozone concentration is increasing linearly within the specified period. The return level of ozone concentration after 10, 25, 50, and 100 years have been forecasted and showed that there was an increasing trend in ozone extremes. High spatial variability of ozone extreme was observed, and those areas around the territories were having extreme ozone concentration than the centers. Moreover, Bayesian Kriging brought about relatively the minimum RMSE compared to the other models. Conclusion. The extreme ozone concentration has clearly showed a positive trend and spatial variation. Moreover, among the models considered in the paper, the Bayesian Kriging has been chosen as the better model.
      PubDate: Fri, 27 Nov 2020 14:20:01 +000
  • Long-Term Homogeneity and Trends of Hydroclimatic Variables in Upper Awash
           River Basin, Ethiopia

    • Abstract: Understanding long-term trends in hydroclimatic variables is important for future sustainable water resource management as it could show the possible regime shifts in hydrology. The main objective of this study was to analyze the homogeneity and trends of hydroclimatic data of Upper Awash Sab-Basin (UASB) in Oromia, Ethiopia, by employing homogeneity tests and Mann-Kendall and Sen’s slope tests. The data consist of 18 rainfall stations, 8 temperature stations, and 8 flow gauging stations across the UASB. Homogeneity and trends in streamflow, rainfall, and temperature variables were analyzed for the time period 1980 to 2017. In order to analyze homogeneity of hydroclimatic variables, we used four homogeneity tests (Pettitt’s test, Buishand’s test, standard normal homogeneity test, and von Neumann ratio test) at 5% significance level. Based on the outputs of four homogeneity tests, the results were classified into three categories, namely, “useful,” “doubtful,” and “suspect” to select the homogeneity stations. Mann-Kendall (Z) and Sen’s slope tests (Q) were applied for the selected homogeneous time series to detect the trend and magnitude of changes in hydroclimatic variables. The result showed that most of the stations in annual rainfall and streamflow data series were classified as useful. It is found that 58% of the rainfall stations were homogeneous. It is highlighted that 3 out of 8 discharge gauging stations have an inhomogeneity as they failed from one or a combination of the four tests. The MK revealed significant decreasing trends of annual rainfall in Addis Alem (Q = −19.81), Akaki (Q = −5.60), Hombole (Q = −9.49), and Ghinch (Q = −12.38) stations. The trend of annual temperature was a significant increasing trend in Addis Ababa Bole (Q = 0.05), Addis Ababa Tikur Ambessa (Q = 0.03), Tulu Bolo (Q = 0.07), and Addis Alem (Q = 0.06) stations. The results of discharge showed a significant increasing trend in Bega at Mojo (Q = 0.17) and Hombole (Q = 0.03) gauging stations. In general, the results obtained from discharge, rainfall, and temperature series indicated that most of the stations exhibited no trends in both annual and seasonal time series. It can be concluded that decreases in average annual rainfall totals and increases in mean annual temperature will probably drive sub-basin scale changes in discharge. We believe that the results obtained can fill information gaps on homogeneity and trends of hydroclimatic variables, which is very crucial for future water resource planning and management in the face of climate change.
      PubDate: Tue, 24 Nov 2020 08:05:01 +000
  • Analysis of Seasonal Daytime Urban Thermal Environment Dynamics in a
           Tropical Coastal City Based on the Spatiotemporal Fusion Model

    • Abstract: This study investigated the seasonal variations of daytime urban thermal environment (UTE) based on land surface temperature (LST) in Shenzhen of 2015. The spatial and temporal adaptive reflectance fusion model (STARFM) was used for retrieving seasonal daytime LST at high spatiotemporal resolution by combining MODIS and HJ-1B LST data. Next, the relationship between the land cover and daytime in each season was examined. Finally, daytime LST patterns were classified, and the effects of seasonal variations of high-grade daytime LSTs were analyzed with landscape metrics. The results showed that (1) the STARFM is capable of generating seasonal daytime LST data at high spatiotemporal resolution. (2) Daytime LSTs were generally higher in the western parts of Shenzhen in spring and summer. (3) Daytime LST in each land cover type showed an increasing trend form winter to summer and decreased from summer to autumn. The highest and lowest daytime LSTs in each season were observed in ISAs and water bodies. (4) Landscape metrics provided a quantitative method for describing seasonal variations in daytime LSTs, and it was found that seasons influenced the intensity and extent of daytime LSTs in Shenzhen. These findings may be helpful for urban planners developing regional urban strategies to improve daytime urban thermal comfort conditions.
      PubDate: Mon, 23 Nov 2020 07:50:01 +000
  • Evaluating the Dependence between Temperature and Precipitation to Better
           Estimate the Risks of Concurrent Extreme Weather Events

    • Abstract: Precipitation and temperature are among major climatic variables that are used to characterize extreme weather events, which can have profound impacts on ecosystems and society. Accurate simulation of these variables at the local scale is essential to adapt urban systems and policies to future climatic changes. However, accurate simulation of these climatic variables is difficult due to possible interdependence and feedbacks among them. In this paper, the concept of copulas was used to model seasonal interdependence between precipitation and temperature. Five copula functions were fitted to grid (approximately 10 km × 10 km) climate data from 1960 to 2013 in southern Ontario, Canada. Theoretical and empirical copulas were then compared with each other to select the most appropriate copula family for this region. Results showed that, of the tested copulas, none of them consistently performed the best over the entire region during all seasons. However, Gumbel copula was the best performer during the winter season, and Clayton performed best in the summer. More variability in terms of best copula was found in spring and fall seasons. By examining the likelihoods of concurrent extreme temperature and precipitation periods including wet/cool in the winter and dry/hot in the summer, we found that ignoring the joint distribution and confounding impacts of precipitation and temperature lead to the underestimation of occurrence of probabilities for these two concurrent extreme modes. This underestimation can also lead to incorrect conclusions and flawed decisions in terms of the severity of these extreme events.
      PubDate: Tue, 17 Nov 2020 14:35:02 +000
  • Evaluating the Performance of Secondary Precipitation Products through
           Statistical and Hydrological Modeling in a Mountainous Tropical Basin of

    • Abstract: This paper investigates the performance of gridded rainfall datasets for precipitation detection and streamflow simulations in Indiaʼs Tungabhadra river basin. Sixteen precipitation datasets categorized under gauge-based, satellite-only, reanalysis, and gauge-adjusted datasets were compared statistically against the gridded Indian Meteorological Dataset (IMD) employing two categorical and three continuous statistical metrics. Further, the precipitation datasets’ performance in simulating streamflow was assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model. Based on the statistical metrics, Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) furnished very good results in terms of detecting rainfall, followed by Climate Hazards Group Infrared Precipitation (CHIRP), National Centres for Environmental Prediction-Climate Forecast System Reanalysis (NCEP CFSR), Tropical Rainfall Measurement Mission (TRMM) 3B42 v7, Global Satellite Mapping of Precipitation Gauge Reanalysis v6 (GSMaP_Gauge_RNL), and Multisource Weighted Ensemble Precipitation (MSWEP) datasets which had good-to-moderate performances at a monthly time step. From the hydrological simulations, TRMM 3B42 v7, CHIRP, CHIRPS 0.05°, and GSMaP_Gauge_RNL v6 produced very good results with a high degree of correlation to observed streamflow, while Soil Moisture 2 Rain-Climate Change Initiative (SM2RAIN-CCI) dataset exhibited poor performance. From the extreme flow event analysis, it was observed that CHIRP, TRMM 3B42 v7, Global Precipitation Climatology Centre v7 (GPCC), and APHRODITE datasets captured more peak flow events and hence can be further implemented for extreme event analysis. Overall, we found that TRMM 3B42 v7, CHIRP, and CHIRPS 0.05° datasets performed better than other datasets and can be used for hydrological modeling and climate change studies in similar topographic and climatic watersheds in India.
      PubDate: Tue, 17 Nov 2020 13:50:01 +000
  • Impact of Multivariate Background Error Covariance on the WRF-3DVAR
           Assimilation for the Yellow Sea Fog Modeling

    • Abstract: Numerical modeling of sea fog is highly sensitive to initial conditions, especially to moisture in the marine atmospheric boundary layer (MABL). Data assimilation plays a vital role in the improvement of initial MABL moisture for sea fog modeling over the Yellow Sea. In this study, the weather research and forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation module are employed for sea fog simulations. Two kinds of background error (BE) covariances with different control variables (CV) used in WRF-3DVAR, that is, CV5 and multivariate BE (CV6), are compared in detail by explorative case studies and a series of application experiments. Statistical verification metrics including probability of detection (POD) and equitable threat scores (ETS) of forecasted sea fog area are computed and compared for simulations with the implementations of CV5 and CV6 in the WRF-3DVAR system. The following is found: (1) there exists a dominant negative correlation between temperature and moisture in CV6 near the sea surface, which makes it possible to improve the initial moisture condition in the MABL by assimilation of observed temperature; (2) in general, the performance of the WRF-3DVAR assimilation with CV6 is distinctly better, and the results of 10 additional sea fog cases clearly suggest that CV6 is more suitable than CV5 for sea fog modeling. Compared to those with CV5, the average POD and ETS of forecasted sea fog area using 3DVAR with CV6 can be improved by 27.6% and 21.0%, respectively.
      PubDate: Tue, 10 Nov 2020 14:35:01 +000
  • Assessing the Response of Satellite Solar-Induced Chlorophyll Fluorescence
           and NDVI to Impacts of Heat Waves on Winter Wheat in the North China Plain

    • Abstract: Global warming has increased the chance of concurrent extreme climate events (weather or climate events that are rare within their statistical reference distributions in a particular place, such as heat waves, floods, and droughts). Crops grow best within specific temperature intervals, and excessive heat is detrimental to the physiological processes of crops and eventually affects yield levels. Analysing historical changes in concurrent extreme high temperatures is critical to preparing for and mitigating the negative effects of climatic change. The North China Plain (NCP) is the most important wheat production area in China. In this study, the spatiotemporal variations in temperature and heat wave trends in the NCP were analysed. Furthermore, we examined the potential of solar-induced chlorophyll fluorescence (SIF) to capture the influence of heat wave impacts on wheat crops in the NCP by comparing satellite remote sensing data of SIF and normalized difference vegetation index (NDVI) and validated ground-based yield data. The results indicate that temperatures and the number of heat wave days in the study region all show increasing trends, especially daily minimum temperature, which has increased by 0.38°C per decade for the past 30 years. Spatially, the southern NCP has suffered greater increasing-temperature trends and more heat wave days than the northern region. Regarding the response of SIF and NDVI to heat waves, SIF can better capture wheat yield decline due to heat waves compared to NDVI; thus, the SIF result indicated more sensitivity to heat waves compared to NDVI.
      PubDate: Thu, 29 Oct 2020 13:50:00 +000
  • Evaluation of Future Climate and Potential Impact on Streamflow in the
           Upper Nan River Basin of Northern Thailand

    • Abstract: Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.
      PubDate: Sat, 24 Oct 2020 08:05:01 +000
  • Changes in Extreme Precipitation in the Mekong Basin

    • Abstract: Extreme precipitation events can trigger many natural disasters like floods, mudslides, and landslides. Understanding historical changes in extreme precipitation is critical for disaster prevention and risk assessment. The Mekong River Basin (MB) is vulnerable to natural disasters related to extreme precipitation. In the past ten years, the MB has experienced some destructive extreme precipitation events. Our concern is whether the historical extreme precipitation events in the MB have increased in a warming climate. This study investigates the spatiotemporal changes in extreme precipitation in the MB from 1951 to 2015 using a high-quality precipitation product and eight indices of extreme precipitation. These indices consistently indicate that the trend in extreme precipitation in the Upper Mekong Basin (UMB) is opposite to that in the Lower Mekong Basin (LMB). Extreme precipitation has generally decreased in the UMB but increased in the LMB. The areas with significant increasing extreme precipitation are mainly located in Laos, Vietnam, and Cambodia. The areas with a statistically significant decline in extreme precipitation primarily occur in the Lancang (China’s section of the Mekong river) and Thailand. Also, the magnitude of changes in extreme precipitation is significantly larger in the LMB than that in the UMB, which potentially increases flooding risks in the LMB. The findings from this study are useful for guiding disaster-prevention efforts in the MB.
      PubDate: Thu, 22 Oct 2020 16:05:01 +000
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