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Publisher: Hindawi   (Total: 335 journals)

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Showing 1 - 200 of 335 Journals sorted alphabetically
Abstract and Applied Analysis     Open Access   (Followers: 3, SJR: 0.343, CiteScore: 1)
Active and Passive Electronic Components     Open Access   (Followers: 7, SJR: 0.136, CiteScore: 0)
Advances in Acoustics and Vibration     Open Access   (Followers: 33, SJR: 0.147, CiteScore: 0)
Advances in Aerospace Engineering     Open Access   (Followers: 52)
Advances in Agriculture     Open Access   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Astronomy     Open Access   (Followers: 38, SJR: 0.257, CiteScore: 1)
Advances in Bioinformatics     Open Access   (Followers: 17, SJR: 0.565, CiteScore: 2)
Advances in Biology     Open Access   (Followers: 8)
Advances in Chemistry     Open Access   (Followers: 21)
Advances in Civil Engineering     Open Access   (Followers: 39, SJR: 0.539, CiteScore: 1)
Advances in Computer Engineering     Open Access   (Followers: 4)
Advances in Condensed Matter Physics     Open Access   (Followers: 10, SJR: 0.315, CiteScore: 1)
Advances in Decision Sciences     Open Access   (Followers: 3, SJR: 0.303, CiteScore: 1)
Advances in Electrical Engineering     Open Access   (Followers: 26)
Advances in Electronics     Open Access   (Followers: 67)
Advances in Emergency Medicine     Open Access   (Followers: 12)
Advances in Endocrinology     Open Access   (Followers: 5)
Advances in Environmental Chemistry     Open Access   (Followers: 5)
Advances in Epidemiology     Open Access   (Followers: 8)
Advances in Fuzzy Systems     Open Access   (Followers: 5, SJR: 0.161, CiteScore: 1)
Advances in Geology     Open Access   (Followers: 14)
Advances in Geriatrics     Open Access   (Followers: 5)
Advances in Hematology     Open Access   (Followers: 11, SJR: 0.661, CiteScore: 2)
Advances in Hepatology     Open Access   (Followers: 2)
Advances in High Energy Physics     Open Access   (Followers: 19, SJR: 0.866, CiteScore: 2)
Advances in Human-Computer Interaction     Open Access   (Followers: 20, SJR: 0.186, CiteScore: 1)
Advances in Materials Science and Engineering     Open Access   (Followers: 30, SJR: 0.315, CiteScore: 1)
Advances in Mathematical Physics     Open Access   (Followers: 4, SJR: 0.218, CiteScore: 1)
Advances in Medicine     Open Access   (Followers: 2)
Advances in Meteorology     Open Access   (Followers: 20, SJR: 0.48, CiteScore: 1)
Advances in Multimedia     Open Access   (Followers: 1, SJR: 0.173, CiteScore: 1)
Advances in Nonlinear Optics     Open Access   (Followers: 6)
Advances in Numerical Analysis     Open Access   (Followers: 5)
Advances in Nursing     Open Access   (Followers: 26)
Advances in Operations Research     Open Access   (Followers: 12, SJR: 0.205, CiteScore: 1)
Advances in Optical Technologies     Open Access   (Followers: 3, SJR: 0.214, CiteScore: 1)
Advances in Optics     Open Access   (Followers: 3)
Advances in OptoElectronics     Open Access   (Followers: 6, SJR: 0.141, CiteScore: 0)
Advances in Orthopedics     Open Access   (Followers: 8, SJR: 0.922, CiteScore: 2)
Advances in Pharmacological Sciences     Open Access   (Followers: 7, SJR: 0.591, CiteScore: 2)
Advances in Physical Chemistry     Open Access   (Followers: 9, SJR: 0.179, CiteScore: 1)
Advances in Power Electronics     Open Access   (Followers: 29, SJR: 0.184, CiteScore: 0)
Advances in Preventive Medicine     Open Access   (Followers: 5)
Advances in Public Health     Open Access   (Followers: 23)
Advances in Software Engineering     Open Access   (Followers: 10)
Advances in Statistics     Open Access   (Followers: 4)
Advances in Toxicology     Open Access   (Followers: 2)
Advances in Tribology     Open Access   (Followers: 12, SJR: 0.265, CiteScore: 1)
Advances in Urology     Open Access   (Followers: 9, SJR: 0.51, CiteScore: 1)
Advances in Virology     Open Access   (Followers: 7, SJR: 0.838, CiteScore: 2)
AIDS Research and Treatment     Open Access   (Followers: 3, SJR: 0.758, CiteScore: 2)
Analytical Cellular Pathology     Open Access   (Followers: 2, SJR: 0.886, CiteScore: 2)
Anatomy Research Intl.     Open Access   (Followers: 2)
Anemia     Open Access   (Followers: 5, SJR: 0.669, CiteScore: 2)
Anesthesiology Research and Practice     Open Access   (Followers: 14, SJR: 0.501, CiteScore: 1)
Applied and Environmental Soil Science     Open Access   (Followers: 16, SJR: 0.451, CiteScore: 1)
Applied Bionics and Biomechanics     Open Access   (Followers: 8, SJR: 0.288, CiteScore: 1)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Archaea     Open Access   (Followers: 3, SJR: 0.852, CiteScore: 2)
Arthritis     Open Access   (Followers: 5, SJR: 0.454, CiteScore: 1)
Autism Research and Treatment     Open Access   (Followers: 25)
Autoimmune Diseases     Open Access   (Followers: 3, SJR: 0.805, CiteScore: 2)
Behavioural Neurology     Open Access   (Followers: 9, SJR: 0.786, CiteScore: 2)
Biochemistry Research Intl.     Open Access   (Followers: 6, SJR: 0.437, CiteScore: 2)
Bioinorganic Chemistry and Applications     Open Access   (Followers: 10, SJR: 0.419, CiteScore: 2)
BioMed Research Intl.     Open Access   (Followers: 4, SJR: 0.935, CiteScore: 3)
Biotechnology Research Intl.     Open Access   (Followers: 1)
Bone Marrow Research     Open Access   (Followers: 2, SJR: 0.531, CiteScore: 1)
Canadian J. of Gastroenterology & Hepatology     Open Access   (Followers: 5, SJR: 0.867, CiteScore: 1)
Canadian J. of Infectious Diseases and Medical Microbiology     Open Access   (Followers: 5, SJR: 0.548, CiteScore: 1)
Canadian Respiratory J.     Open Access   (Followers: 1, SJR: 0.474, CiteScore: 1)
Cardiology Research and Practice     Open Access   (Followers: 8, SJR: 1.237, CiteScore: 4)
Case Reports in Anesthesiology     Open Access   (Followers: 10)
Case Reports in Cardiology     Open Access   (Followers: 3, SJR: 0.219, CiteScore: 0)
Case Reports in Critical Care     Open Access   (Followers: 8)
Case Reports in Dentistry     Open Access   (Followers: 5, SJR: 0.229, CiteScore: 0)
Case Reports in Dermatological Medicine     Open Access   (Followers: 2)
Case Reports in Emergency Medicine     Open Access   (Followers: 14)
Case Reports in Endocrinology     Open Access   (Followers: 1, SJR: 0.209, CiteScore: 1)
Case Reports in Gastrointestinal Medicine     Open Access   (Followers: 2)
Case Reports in Genetics     Open Access   (Followers: 1)
Case Reports in Hematology     Open Access   (Followers: 5)
Case Reports in Hepatology     Open Access   (Followers: 1)
Case Reports in Immunology     Open Access   (Followers: 4)
Case Reports in Infectious Diseases     Open Access   (Followers: 5)
Case Reports in Medicine     Open Access   (Followers: 2)
Case Reports in Nephrology     Open Access   (Followers: 4)
Case Reports in Neurological Medicine     Open Access   (Followers: 1)
Case Reports in Obstetrics and Gynecology     Open Access   (Followers: 10)
Case Reports in Oncological Medicine     Open Access   (Followers: 2, SJR: 0.204, CiteScore: 1)
Case Reports in Ophthalmological Medicine     Open Access   (Followers: 3)
Case Reports in Orthopedics     Open Access   (Followers: 5)
Case Reports in Otolaryngology     Open Access   (Followers: 6)
Case Reports in Pathology     Open Access   (Followers: 5)
Case Reports in Pediatrics     Open Access   (Followers: 6)
Case Reports in Psychiatry     Open Access   (Followers: 13)
Case Reports in Pulmonology     Open Access   (Followers: 3)
Case Reports in Radiology     Open Access   (Followers: 8)
Case Reports in Rheumatology     Open Access   (Followers: 6)
Case Reports in Surgery     Open Access   (Followers: 11)
Case Reports in Transplantation     Open Access  
Case Reports in Urology     Open Access   (Followers: 8)
Case Reports in Vascular Medicine     Open Access  
Case Reports in Veterinary Medicine     Open Access   (Followers: 6)
Child Development Research     Open Access   (Followers: 18, SJR: 0.144, CiteScore: 0)
Chinese J. of Engineering     Open Access   (Followers: 2, SJR: 0.114, CiteScore: 0)
Chinese J. of Mathematics     Open Access  
Cholesterol     Open Access   (Followers: 1, SJR: 0.424, CiteScore: 1)
Chromatography Research Intl.     Open Access   (Followers: 6)
Complexity     Hybrid Journal   (Followers: 6, SJR: 0.531, CiteScore: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2, SJR: 0.403, CiteScore: 1)
Computational Intelligence and Neuroscience     Open Access   (Followers: 10, SJR: 0.326, CiteScore: 1)
Contrast Media & Molecular Imaging     Open Access   (Followers: 3, SJR: 0.842, CiteScore: 3)
Critical Care Research and Practice     Open Access   (Followers: 10, SJR: 0.499, CiteScore: 1)
Current Gerontology and Geriatrics Research     Open Access   (Followers: 9, SJR: 0.512, CiteScore: 2)
Depression Research and Treatment     Open Access   (Followers: 13, SJR: 0.816, CiteScore: 2)
Dermatology Research and Practice     Open Access   (Followers: 3, SJR: 0.806, CiteScore: 2)
Diagnostic and Therapeutic Endoscopy     Open Access   (SJR: 0.201, CiteScore: 1)
Discrete Dynamics in Nature and Society     Open Access   (Followers: 5, SJR: 0.279, CiteScore: 1)
Disease Markers     Open Access   (Followers: 1, SJR: 0.9, CiteScore: 2)
Economics Research Intl.     Open Access   (Followers: 1)
Education Research Intl.     Open Access   (Followers: 19)
Emergency Medicine Intl.     Open Access   (Followers: 8, SJR: 0.298, CiteScore: 1)
Enzyme Research     Open Access   (Followers: 3, SJR: 0.653, CiteScore: 3)
Evidence-based Complementary and Alternative Medicine     Open Access   (Followers: 18, SJR: 0.683, CiteScore: 2)
Game Theory     Open Access   (Followers: 1)
Gastroenterology Research and Practice     Open Access   (Followers: 2, SJR: 0.768, CiteScore: 2)
Genetics Research Intl.     Open Access   (Followers: 1, SJR: 0.61, CiteScore: 2)
Geofluids     Open Access   (Followers: 4, SJR: 0.952, CiteScore: 2)
Hepatitis Research and Treatment     Open Access   (Followers: 6, SJR: 0.389, CiteScore: 2)
HPB Surgery     Open Access   (Followers: 5, SJR: 0.824, CiteScore: 2)
Infectious Diseases in Obstetrics and Gynecology     Open Access   (Followers: 5, SJR: 1.27, CiteScore: 2)
Interdisciplinary Perspectives on Infectious Diseases     Open Access   (Followers: 1, SJR: 0.627, CiteScore: 2)
Intl. J. of Aerospace Engineering     Open Access   (Followers: 73, SJR: 0.232, CiteScore: 1)
Intl. J. of Agronomy     Open Access   (Followers: 6, SJR: 0.311, CiteScore: 1)
Intl. J. of Alzheimer's Disease     Open Access   (Followers: 11, SJR: 0.787, CiteScore: 3)
Intl. J. of Analysis     Open Access  
Intl. J. of Analytical Chemistry     Open Access   (Followers: 20, SJR: 0.285, CiteScore: 1)
Intl. J. of Antennas and Propagation     Open Access   (Followers: 11, SJR: 0.233, CiteScore: 1)
Intl. J. of Atmospheric Sciences     Open Access   (Followers: 21)
Intl. J. of Biodiversity     Open Access   (Followers: 4)
Intl. J. of Biomaterials     Open Access   (Followers: 4, SJR: 0.511, CiteScore: 2)
Intl. J. of Biomedical Imaging     Open Access   (Followers: 3, SJR: 0.501, CiteScore: 2)
Intl. J. of Breast Cancer     Open Access   (Followers: 13, SJR: 1.025, CiteScore: 2)
Intl. J. of Cell Biology     Open Access   (Followers: 3, SJR: 1.887, CiteScore: 4)
Intl. J. of Chemical Engineering     Open Access   (Followers: 7, SJR: 0.327, CiteScore: 1)
Intl. J. of Chronic Diseases     Open Access   (Followers: 1)
Intl. J. of Combinatorics     Open Access   (Followers: 1)
Intl. J. of Computer Games Technology     Open Access   (Followers: 9, SJR: 0.287, CiteScore: 2)
Intl. J. of Corrosion     Open Access   (Followers: 10, SJR: 0.194, CiteScore: 1)
Intl. J. of Dentistry     Open Access   (Followers: 6, SJR: 0.649, CiteScore: 2)
Intl. J. of Differential Equations     Open Access   (Followers: 7, SJR: 0.191, CiteScore: 0)
Intl. J. of Digital Multimedia Broadcasting     Open Access   (Followers: 5, SJR: 0.296, CiteScore: 2)
Intl. J. of Electrochemistry     Open Access   (Followers: 8)
Intl. J. of Endocrinology     Open Access   (Followers: 4, SJR: 1.012, CiteScore: 3)
Intl. J. of Engineering Mathematics     Open Access   (Followers: 5)
Intl. J. of Food Science     Open Access   (Followers: 3, SJR: 0.44, CiteScore: 2)
Intl. J. of Forestry Research     Open Access   (Followers: 3, SJR: 0.373, CiteScore: 1)
Intl. J. of Genomics     Open Access   (Followers: 2, SJR: 0.868, CiteScore: 3)
Intl. J. of Geophysics     Open Access   (Followers: 4, SJR: 0.182, CiteScore: 1)
Intl. J. of Hepatology     Open Access   (Followers: 4, SJR: 0.874, CiteScore: 2)
Intl. J. of Hypertension     Open Access   (Followers: 6, SJR: 0.578, CiteScore: 1)
Intl. J. of Inflammation     Open Access   (SJR: 1.264, CiteScore: 3)
Intl. J. of Inorganic Chemistry     Open Access   (Followers: 3)
Intl. J. of Manufacturing Engineering     Open Access   (Followers: 2)
Intl. J. of Mathematics and Mathematical Sciences     Open Access   (Followers: 3, SJR: 0.177, CiteScore: 0)
Intl. J. of Medicinal Chemistry     Open Access   (Followers: 6, SJR: 0.31, CiteScore: 1)
Intl. J. of Metals     Open Access   (Followers: 4)
Intl. J. of Microbiology     Open Access   (Followers: 4, SJR: 0.662, CiteScore: 2)
Intl. J. of Microwave Science and Technology     Open Access   (Followers: 3, SJR: 0.136, CiteScore: 1)
Intl. J. of Navigation and Observation     Open Access   (Followers: 20, SJR: 0.267, CiteScore: 2)
Intl. J. of Nephrology     Open Access   (Followers: 1, SJR: 0.697, CiteScore: 1)
Intl. J. of Oceanography     Open Access   (Followers: 7)
Intl. J. of Optics     Open Access   (Followers: 7, SJR: 0.231, CiteScore: 1)
Intl. J. of Otolaryngology     Open Access   (Followers: 3)
Intl. J. of Partial Differential Equations     Open Access   (Followers: 2)
Intl. J. of Pediatrics     Open Access   (Followers: 6)
Intl. J. of Peptides     Open Access   (Followers: 4, SJR: 0.46, CiteScore: 1)
Intl. J. of Photoenergy     Open Access   (Followers: 2, SJR: 0.341, CiteScore: 1)
Intl. J. of Plant Genomics     Open Access   (Followers: 4, SJR: 0.583, CiteScore: 1)
Intl. J. of Polymer Science     Open Access   (Followers: 24, SJR: 0.298, CiteScore: 1)
Intl. J. of Population Research     Open Access   (Followers: 2)
Intl. J. of Quality, Statistics, and Reliability     Open Access   (Followers: 15)
Intl. J. of Reconfigurable Computing     Open Access   (SJR: 0.123, CiteScore: 1)
Intl. J. of Reproductive Medicine     Open Access   (Followers: 4)
Intl. J. of Rheumatology     Open Access   (Followers: 4, SJR: 0.645, CiteScore: 2)
Intl. J. of Rotating Machinery     Open Access   (Followers: 2, SJR: 0.193, CiteScore: 1)
Intl. J. of Spectroscopy     Open Access   (Followers: 7)
Intl. J. of Stochastic Analysis     Open Access   (Followers: 3, SJR: 0.279, CiteScore: 1)
Intl. J. of Surgical Oncology     Open Access   (Followers: 1, SJR: 0.573, CiteScore: 2)
Intl. J. of Telemedicine and Applications     Open Access   (Followers: 4, SJR: 0.403, CiteScore: 2)
Intl. J. of Vascular Medicine     Open Access   (SJR: 0.782, CiteScore: 2)
Intl. J. of Zoology     Open Access   (Followers: 2, SJR: 0.209, CiteScore: 1)
Intl. Scholarly Research Notices     Open Access   (Followers: 190)
ISRN Astronomy and Astrophysics     Open Access   (Followers: 6)
J. of Addiction     Open Access   (Followers: 12)
J. of Advanced Transportation     Hybrid Journal   (Followers: 13, SJR: 0.581, CiteScore: 1)
J. of Aerodynamics     Open Access   (Followers: 5)
J. of Aging Research     Open Access   (Followers: 6, SJR: 0.573, CiteScore: 2)

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Journal Cover
Advances in Meteorology
Journal Prestige (SJR): 0.48
Citation Impact (citeScore): 1
Number of Followers: 20  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1687-9309 - ISSN (Online) 1687-9317
Published by Hindawi Homepage  [335 journals]
  • Vertical Structure of Moisture Content over Europe

    • Abstract: The vertical structure of water vapor content in the atmosphere strongly affects the amount of solar radiation reaching the Earth’s surface and processes associated with the formation of clouds and atmospheric precipitation. The purpose of this study was to assess the vertical differentiation of water vapor over Europe on a seasonal basis and also to evaluate the role of atmospheric circulation in changes therein. Daily values of specific humidity (SHUM) for the time period 1981–2015 were obtained from pressure levels available from ECMWF Era-Interim reanalysis data and used in the study. Eight grid points were analyzed in detail. Each point is representative of a region with different moisture conditions. SHUM profiles were then used to identify cases of moisture inversion. Horizontal flux of specific humidity (SHUMF) was analyzed for principal pressure levels that occur in both inversion-type and inversion-free situations. In addition, SHUM and SHUMF anomalies were identified for advection directions. The research results showed the existence of differences in the vertical structure of water vapor content in the troposphere over Europe, and the Northeastern Atlantic and the presence of moisture inversions not only in areas north of 60°N but also in temperate and subtropical zones. Inversions can occur in two different forms—surface-based and elevated. The occurrence of inversions varies with the seasons. The role of atmospheric circulation is observable in the winter and triggers both surpluses and shortages of moisture via the effect of specific pressure system types (significant role of seasonal pressure high) and via advection directions. In addition, there exists a clear difference between the structure of moisture in the atmospheric boundary layer and in the free atmosphere.
      PubDate: Thu, 12 Jul 2018 00:00:00 +000
  • Temporal Trends and Spatial Patterns of Temperature and Its Extremes over
           the Beijing-Tianjin Sand Source Region (1960–2014), China

    • Abstract: In order to examine temperature changes and extremes in the Beijing-Tianjin Sand Source Region (BTSSR), ten extreme temperature indices were selected, categorized, and calculated spanning the period 1960–2014, and the spatiotemporal variability and trends of temperature and extremes on multitimescales in the BTSSR were investigated using the Mann-Kendall (M-K) test, Sen’s slope estimator, and linear regression. Results show that mean temperatures have increased and extreme temperature events have become more frequent. Annual temperature has recorded a significant increasing trend over the BTSSR, in which 51 stations exhibited significant increasing trends (); winter temperature recorded the most significant increasing trend in the northwest subregion. All extreme temperature indices showed warming trends at most stations; a higher warming slope in extreme temperature mainly occurred along the northeast border and northwest border and in the central-southern mountain area. As extreme low temperature events decrease, vegetation damage due to freezing temperatures will reduce and low cold-tolerant plants may expand their distribution range northward to revegetate barren areas in the BTSSR. However, in water-limited areas of the BTSSR, increasing temperatures in the growing season may exacerbate stress associated with plants relying on precipitation due to higher temperatures combining with decreasing precipitation.
      PubDate: Tue, 10 Jul 2018 00:00:00 +000
  • Estimation of Actual Evapotranspiration Distribution in the Huaihe River
           Upstream Basin Based on the Generalized Complementary Principle

    • Abstract: The accurate estimation of actual evapotranspiration can help improve the utilization of water resources and ease the ecological stress. Based on the generalized complementary principle proposed by Brutsaert in 2015, we used meteorological and hydrological data to estimate the actual evapotranspiration at a resolution of 1 km × 1 km between the years of 1961 and 2000 and also verified the model’s stability. In this study, we used the water balance equation to calibrate the parameters, coupled with the spatial simulation results of the meteorological elements in the actual evapotranspiration model. The estimation results of actual evapotranspiration show that the generalized complementary principle model had high estimation precision in this basin, with an average absolute error of 16.64 mm and an average relative error of 2.25%. With respect to spatial distribution, the average actual evapotranspiration over the years in the basin tended to have high and low distribution in the northern and southern parts of the basin, respectively. The actual evapotranspiration in the basin showed a decreasing trend over the period, with a rate of 24.1 mm/10 years. Correlation coefficient analysis showed that the percentage decreases in percentage sunshine and the decreases in the daily range of temperature were the main reasons for the decrease in actual evapotranspiration.
      PubDate: Sun, 08 Jul 2018 00:00:00 +000
  • Accuracy Analysis of the Aerosol Backscatter Coefficient Profiles Derived
           from the CYY-2B Ceilometer

    • Abstract: Ceilometers are originally designed for cloud base height monitoring. Since a few years, the number of ceilometers available worldwide is rapidly increasing, and these simple backscatter lidars are investigated to be used for aerosol research. This study presents an assessment of the potential of CYY-2B ceilometer for the quantitative retrieval of aerosol properties. The signal-to-noise ratio of the ceilometer is calculated, and the effective height of inversion is determined. It is shown that the effective height of the ceilometer for backscatter coefficient profile inversion is 3-4 km at night and about 1.5–2 km during the day, which is lower than that of the micropulse lidar (MPL) system. The accuracy of the backscatter coefficient profiles derived from the CYY-2B ceilometer is analyzed by using the Vaisala CL51 ceilometer, MPL, forward scatter visibility instrument, and aerosol optical depth (AOD) dataset from aerosol robotic network (AERONET). Spectral conversions of the ceilometer’s and lidar’s data are performed using the Ångström exponent estimated by AERONET measurements. A good agreement is found between two ceilometers and the MPL lidar in backscatter coefficient profiles inversion. The AODs agree well with the AERONET AODs during the observation period of small AODs. However, for the period of large AODs, the results are approximately 50%–60% of AERONET AODs. The limited range of extinction integration is the main cause of this problem.
      PubDate: Sun, 08 Jul 2018 00:00:00 +000
  • Flood Simulation in South Carolina Watersheds Using Different
           Precipitation Inputs

    • Abstract: Flooding induced by extreme rainfall events causes tremendous loss of life and property and infrastructure failure. Accurate representation of precipitation, which has high variation in space and time, is critical to hydrologic model simulations and flood analyses. In this study, we examined responses of differently sized United States Geological Survey (USGS) hydrologic units to heavy precipitation using three different data sets. The first consists of rainfall observed at individual meteorological gauges. The second uses the National Centers for Environmental Prediction (NCEP) Environmental Modeling Center (EMC) 4 km gridded radar-estimated precipitation (GRIB) Stage IV data. The third one derives from the method we developed that blends gauge data with the spatial coverage of the Parameter-elevation Relationships on Independent Slopes Model (PRISM) data. We examined how two watersheds in South Carolina respond to the three different representations of heavy rainfall, using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) developed by the U.S. Army Corps of Engineers. We found that the latter two precipitation inputs that consider spatial representation of rainfall yielded similar performance and improved simulated streamflow as compared to simulation using rainfall observed at individual meteorological gauges. The method we developed overcomes the spatial sparsity of rain gauges required for interpolation and extends availability of precipitation surfaces. Our study advances the understanding of advantages and limitations of different precipitation products for flood simulation.
      PubDate: Thu, 05 Jul 2018 02:36:57 +000
  • Solar Radiation Models and Gridded Databases to Fill Gaps in Weather
           Series and to Project Climate Change in Brazil

    • Abstract: The quantification of climate change impacts on several human activities depends on reliable weather data series, without gaps and long enough to build up future climate. Based on that, this study aimed to evaluate the performance of temperature-based models for estimating global solar radiation and gridded databases (AgCFSR, AgMERRA, NASA/POWER, and XAVIER) as alternative ways for filling gaps in historical weather series (1980–2009) in Brazil and to project climate change scenarios based on measured and gridded weather data. Projections for mid- and end-of-century periods (2040–2069 and 2070–2099), using seven global climate models from CMIP5 under intermediate (RCP4.5) and high (RCP8.5) emission scenarios, were performed. The Bristow–Campbell model was the one that best estimated solar radiation, whereas the XAVIER gridded database was the closest to observed weather data. Future climate projections, under RCP4.5 and RCP8.5 scenarios, as expected, showed warmer conditions for all scenarios over Brazil. On the contrary, rainfall projections are more uncertain. Despite that, the rainfall amounts will be reduced in the North-Northeast region and increased in Southern Brazil. No significant differences between projections using the observed and XAVIER gridded database were observed; therefore, such a database showed to be reliable for both to fill gaps and to generate climate change scenarios.
      PubDate: Thu, 05 Jul 2018 00:33:17 +000
  • Predictive Contributions of Snowmelt and Rainfall to Streamflow Variations
           in the Western United States

    • Abstract: This study used long-term in situ rainfall, snow, and streamflow data to explore the predictive contributions of snowmelt and rainfall to streamflow in six watersheds over the Western United States. Analysis showed that peak snow accumulation, snow-free day, and snowmelt slope all had strong correlation with peak streamflow, particularly in inland basins. Further analysis revealed that the variation of snow accumulation anomaly had strong lead correlation with the variation of streamflow anomaly. Over the entire Western United States, inner mountain areas had lead times of 4–10 pentads. However, in coastal areas, nearly all sites had lead times of less than one pentad. The relative contributions of rainfall and snowmelt to streamflow in different watersheds were calculated based on the snow lead time. The geographic distribution of annual relative contributions revealed that interior areas were dominated by snowmelt contribution, whereas the rainfall contribution dominated coastal areas. In the wet season, the snowmelt contribution increased in the western Pacific Northwest, whereas the rainfall contribution increased in the southeastern Pacific Northwest, southern Upper Colorado, and northern Rio Grande regions. The derived results demonstrated the predictive contributions of snowmelt and rainfall to streamflow. These findings could be considered a reference both for seasonal predictions of streamflow and for prevention of hydrological disasters. Furthermore, they will be helpful in the evaluation and improvement of hydrological and climate models.
      PubDate: Wed, 04 Jul 2018 09:46:56 +000
  • Assimilation of Doppler Radar Data and Its Impact on Prediction of a Heavy
           Meiyu Frontal Rainfall Event

    • Abstract: Operational Doppler radar observations have potential advantages over other above-surface observations when it comes to assimilation for mesoscale model simulations with high spatial and temporal resolution. To improve the forecast of a heavy frontal rainfall event that occurred in the Yangtze-Huaihe River Basin from 4 July to 5 July 2014 in China, operational radar observations are assimilated by the Local Analysis and Prediction System (LAPS). Radar reflectivity data are used primarily in the LAPS cloud analysis procedure, which retrieves the number of hydrometeors and adjusts the moisture and cloud fields. Radial velocity data are analyzed through the LAPS wind analysis-based successive correction method. A new correction method is developed to correct three-dimensional radar reflectivity data based on hourly surface rain gauge observations. The performance of the correction method is demonstrated by assimilating radar reflectivity observations into LAPS. Experiments with different radar data assimilation are examined. Results show that the assimilation of radar data can effectively correct the background errors and improve the heavy rainfall forecast. The simulated intensity, pattern, and temporal evolution of the heavy rainfall event are better improved with radar reflectivity assimilation, especially when the correction method is implemented to correct radar observations.
      PubDate: Thu, 28 Jun 2018 08:36:11 +000
  • Experimental, Observational, and Numerical Research on Intentional and
           Inadvertent Weather Modification

    • PubDate: Thu, 28 Jun 2018 05:15:56 +000
  • Detecting Anomalies in Meteorological Data Using Support Vector Regression

    • Abstract: Significant errors exist in automated meteorological data, and identifying them is very important. In this paper, we present a novel method for determining abnormal values in meteorological observations based on support vector regression (SVR). SVR is used to predict the observation value from a spatial perspective. The difference between the estimated value and the actual observed value determines if the observed value is abnormal or not. In addition, SVR input variables are deliberately selected to improve SVR performance and shorten computing time. In the selection process, a multiobjective genetic algorithm is used to optimize the two objective functions. In experiments using real-world data sets collected from accredited agencies, the proposed estimation method using SVR reduced the RMSE by an average of 45.44% whilst maintaining competitive computing times compared to baseline estimators.
      PubDate: Tue, 26 Jun 2018 00:00:00 +000
  • Spatiotemporal Variability of Arctic Soil Moisture Detected from
           High-Resolution RADARSAT-2 SAR Data

    • Abstract: Various methods are used to determine soil moisture information from synthetic aperture radar (SAR) data, but none specific to High Arctic regions and their unique physical characteristics. This research presents a method for determining, at high spatial and temporal resolutions, surface soil moisture and its changes through time in the Canadian High Arctic. An artificial neural network (ANN) is implemented using input variables derived from RADARSAT-2 SAR data and previously modelled surface roughness information. The model is applied to SAR data collected at various incidence angles and acquisition dates across two study sites on Melville Island, Nunavut. The model results in absolute soil moisture errors of approximately 15% (r2 = 0.46) for the primary study sites and 12% (r2 = 0.26) for the verification study area. The ANN model is accurate for modelling (i) the spatial distribution of soil moisture and (ii) the changes in moisture through time across the study areas, two characteristics that are very important for inputs to hydrologic or climate models. In addition, the models appear to be scalable when applied at coarser spatial resolutions, showing potential for large-area mapping or modelling.
      PubDate: Tue, 26 Jun 2018 00:00:00 +000
  • Research on Fusing Multisatellite Soil Moisture Data Based on Bayesian
           Model Averaging

    • Abstract: Soil moisture (SM) is an important physical quantity that can reflect the land surface condition. There are many ways to measure SM, satellite microwave remote sensing is now considered the primary method because it can provide real-time high-resolution data. However, SM data obtained by satellite remote sensing exhibit certain deviation compared with reference data obtained from ground stations. To improve the accuracy of SM forecasts, this study proposed the use of a Bayesian model averaging (BMA) method to integrate multisatellite SM data. First, China was divided into eight regions. Then, SM data observed by satellites (FY3B, SMOS, and WINDSAT) were fused using the BMA method and a traditional averaging method. Finally, SM data were predicted using data from ground observation stations as a reference standard. Following the fusion process, three parameters (standard deviation, correlation coefficient, and root mean square deviation) were used to evaluate the fusion results, which revealed the superiority of the BMA method over the traditional averaging method.
      PubDate: Mon, 25 Jun 2018 04:11:35 +000
  • Human Settlement Quality Evaluation Based on Air Quality in Major Cities
           of China

    • Abstract: Based on the monthly data of 12 months in 30 major cities and combined with the monthly data of the air quality index (AQI) in 30 major cities, this paper analyzed the quality of human settlements in 2015 with the ArcGIS spatial analysis method. On the basis of the quality of air in this analysis, the coupling degree of the five great systems in these human settlements was also calculated. The finding shows that (1) according to the spatial distribution of the human settlements quality index in the main cities, the quality of urban human settlements was gradually decreased from the coastal regions to northwest inland regions, presenting an overall look that the quality was high in the south and low in the north, which converged to the change of the air quality; (2) the human settlements quality index apparently changed with season variation. A significant difference was found in the fourth quarter, and the biggest deviation among cities in China was up to 0.680, while the smallest deviation in the second quarter was 0.448; and (3) on the basis of factors that influenced the quality index, related kinds of norms in the main cities were built in the five great systems of human settlements, and the evaluated coupling degree between the five systems was at the antagonistic stage.
      PubDate: Sun, 24 Jun 2018 07:33:43 +000
  • Temporal-Spatial Characteristics of Drought in Guizhou Province, China,
           Based on Multiple Drought Indices and Historical Disaster Records

    • Abstract: Guizhou Province, China, experienced several severe drought events over the period from 1960 to 2013, causing great economic loss and intractable conflicts over water. In this study, the spatial and temporal characteristics of droughts are analyzed with the standard precipitation index (SPI), comprehensive meteorological drought index (CI), and reconnaissance drought index (RDI). Meanwhile, historical drought records are used to test the performance of each index at identifying droughts. All three indices show decreasing annual and autumn trends, with the latter particularly prominent. 29, 30, and 32 drought events were identified during 1960–2013 by the SPI, CI, and RDI, respectively. Continuous drought is more frequent in winter–spring and summer–autumn. There is a significant increasing trend in drought event frequency, peak, and strength since the start of the 21st century. Drought duration indicated by CI shows longer durations in the higher-elevation region of central and western Guizhou. The corresponding drought severity is high in these regions. SPI and RDI indicate longer drought durations in the lower elevation central and eastern regions of Guizhou Province, where the corresponding drought severity is also very strong. SPI shows an increasing trend in drought duration and drought severity across most of the regions of Guizhou. In general, SPI and RDI show an increasing trend in the western Guizhou Province and a decreasing trend in central and eastern Guizhou. Comparing these three drought indices with historical records, the RDI is found to be more objective and reliable than the SPI and CI when identifying the periods of drought in Guizhou.
      PubDate: Thu, 14 Jun 2018 10:17:41 +000
  • Development of Heavy Rain Damage Prediction Model Using Machine Learning
           Based on Big Data

    • Abstract: Prediction models of heavy rain damage using machine learning based on big data were developed for the Seoul Capital Area in the Republic of Korea. We used data on the occurrence of heavy rain damage from 1994 to 2015 as dependent variables and weather big data as explanatory variables. The model was developed by applying machine learning techniques such as decision trees, bagging, random forests, and boosting. As a result of evaluating the prediction performance of each model, the AUC value of the boosting model using meteorological data from the past 1 to 4 days was the highest at 95.87% and was selected as the final model. By using the prediction model developed in this study to predict the occurrence of heavy rain damage for each administrative region, we can greatly reduce the damage through proactive disaster management.
      PubDate: Wed, 13 Jun 2018 00:00:00 +000
  • A Multiple Kernel Learning Approach for Air Quality Prediction

    • Abstract: Air quality prediction is an important research issue due to the increasing impact of air pollution on the urban environment. However, existing methods often fail to forecast high-polluting air conditions, which is precisely what should be highlighted. In this paper, a novel multiple kernel learning (MKL) model that embodies the characteristics of ensemble learning, kernel learning, and representative learning is proposed to forecast the near future air quality (AQ). The centered alignment approach is used for learning kernels, and a boosting approach is used to determine the proper number of kernels. To demonstrate the performance of the proposed MKL model, its performance is compared to that of classical autoregressive integrated moving average (ARIMA) model; widely used parametric models like random forest (RF) and support vector machine (SVM); popular neural network models like multiple layer perceptron (MLP); and long short-term memory neural network. Datasets acquired from a coastal city Hong Kong and an inland city Beijing are used to train and validate all the models. Experiments show that the MKL model outperforms the other models. Moreover, the MKL model has better forecast ability for high health risk category AQ.
      PubDate: Tue, 12 Jun 2018 09:32:07 +000
  • Severe Weather Events over Southeastern Brazil during the 2016 Dry Season

    • Abstract: Southeastern Brazil is the most populated and economically developed region of this country. Its climate consists of two distinct seasons: the dry season, extending from April to September, the precipitation is significantly reduced in comparison to that of the wet season, which extends from October to March. However, during nine days of the 2016 dry season, successive convective systems were associated with atypical precipitation events, tornadoes and at least one microburst over the southern part of this region. These events led to flooding, damages to buildings, shortages of electricity and water in several places, many injuries, and two documented deaths. The present study investigates the synoptic and dynamical features related to these anomalous events. The convective systems were embedded in an unstable environment with intense low-level jet flow and strong wind shear and were supported by a sequence of extratropical cyclones occurring over the Southwest Atlantic Ocean. These features were intensified by the Madden–Julian oscillation (MJO) in its phase 8 and by intense negative values of the Pacific South America (PSA) 2 mode.
      PubDate: Sun, 10 Jun 2018 09:52:52 +000
  • A Preliminary Assessment of the Impact of Assimilating Satellite Soil
           Moisture Data Products on NCEP Global Forecast System

    • Abstract: It is well documented that soil moisture has a strong impact on precipitation forecasts of numerical weather prediction models. Several microwave satellite soil moisture retrieval data products have also been available for applications. However, these observational data products have not been employed in any operational numerical weather or climate prediction models. In this study, a preliminary test of assimilating satellite soil moisture data products from the NOAA-NESDIS Soil Moisture Operational Product System (SMOPS) into the NOAA-NCEP Global Forecast System (GFS) is conducted. Using the ensemble Kalman filter (EnKF) introduced in recent year publications and implemented in the GFS, the multiple satellite blended daily global soil moisture data from SMOPS for the month of April 2012 are assimilated into the GFS. The forecasts of surface variables, anomaly correlations of isobar heights, and precipitation forecast skills of the GFS with and without the soil moisture data assimilation are assessed. The surface and deep layer soil moisture estimates of the GFS after the satellite soil moisture assimilation are found to have slightly better agreement with the ground soil moisture measurements at dozens of sites across the continental United States (CONUS). Forecasts of surface humidity and air temperature, 500 hPa height anomaly correlations, and the precipitation forecast skill demonstrated certain level of improvements after the soil moisture assimilation against those without the soil moisture assimilation. However, the methodology for the soil moisture data assimilation into operational GFS runs still requires further development efforts and tests.
      PubDate: Sun, 10 Jun 2018 07:28:45 +000
  • ESA CCI Soil Moisture Assimilation in SWAT for Improved Hydrological
           Simulation in Upper Huai River Basin

    • Abstract: The assimilation of satellite soil moisture (SM) products with coarse resolution is promising in improving rainfall-runoff modeling, but it is largely impacted by the data assimilation (DA) strategy. This study performs the assimilation of a satellite soil moisture product from the European Space Agency (ESA) Climate Change Initiative (CCI) in a physically based semidistributed hydrological model (SWAT) in the upper Huai River basin in China, with the objective to improve its rainfall-runoff simulation. In this assimilation, the ensemble Kalman filter (EnKF) is adopted with full consideration of the model and observation error, the rescaling technique for satellite SM, and the regional applicability of the hydrological model. The results show that the ESA CCI SM assimilation generally improves the streamflow simulation of the study catchment. It is more effective for low-flow simulation, while for very high-flow/large-flood modeling, the DA performance shows uncertainty. The less-effective performance on large-flood simulation lies in the relatively low dependence of rainfall-runoff generation on the antecedent SM as during which the SM is nearly saturated and the runoff is largely dominated by precipitation. Besides, the efficiency of DA is deteriorated by the dense forest coverage and the complex topography conditions of the basin. Overall, the ESA CCI SM assimilation improves the streamflow simulation of the SWAT model in particular for low flow. This study provides an encouragement for the application of the ESA CCI SM in water management, especially over low-flow periods.
      PubDate: Thu, 07 Jun 2018 04:27:10 +000
  • Harmonic Analysis of Precipitation Time Series in Lake Tana Basin,

    • Abstract: This study presents harmonic analysis of precipitation observations within the Lake Tana Basin for the periods of 1985–2015. The livelihood of several millions of people within the basin and outside the basin is governed by the precipitation conditions within this basin. Large spatial and temporal variabilities of precipitation can increase the incidence of extreme events such as floods and droughts. It is important to identify the characteristics of these variations, and this study aims at investigating the characteristics of the seasonal and annual cycles of precipitation within the Lake Tana Basin using harmonic analysis. Precipitation data of 31 years from four weather stations were used in the analysis. We then applied harmonic analysis to calculate the amplitude, phase shift, and variance of observation. Detailed characteristics of the first five harmonics are presented and discussed. We found the amplitude of the first harmonic to be and for Debre Tabor, Bahir Dar, Gondar, and Dangila, respectively. This shows that Dangila areas got more rainfall during this fundamental period than others increasing from Gondar to Dangila direction. Also, the variance in the first harmonic is smaller than the variances of other harmonics, and this means that the large variations of the precipitation originate from higher harmonics (short time periods). This shows that precipitation variations are governed mainly by monthly, seasonal, and semiannual variations. The analysis has shown that maximum precipitation for all stations occurred in July and August.
      PubDate: Thu, 07 Jun 2018 00:00:00 +000
  • Spatiotemporal Exploration and Hazard Mapping of Tropical Cyclones along
           the Coastline of China

    • Abstract: Spatiotemporal patterns are one of the greatest interests and provide valuable insights into chronological events occurring in space. A tropical cyclone (TC) track is defined as a sequence of successive points, and several different types of analyses are performed to explore the temporal and spatial patterns of the TCs in the Northwest Pacific and along the coastline of China during 1949–2014. Results show that (1) the number of TCs is getting more frequent from April to August and less frequent from August to October with the peak occurring in August almost every year; (2) the mean of the sizes of the annual temporal clusters during 1949–2014 is 52.5 (days), the standard deviation is 17.0 (days), and the average starting point is the 210.5th day; (3) the spatial clusters are located in two areas: the boundary of Guangxi and Guangdong provinces and the boundary of Fujian and Zhejiang provinces; and (4) the within-strata variance is less than the between-strata variance, which implies the locational and seasonal factors are the potential determinants of the heterogeneity of the TCs. Furthermore, several maps representing the hazards of TCs are produced. According to the resultant maps, 12 coastal prefectures (Zhanjiang, Maoming, Fuzhou, Huizhou, Yangjiang, Qinzhou, Ningde, Quanzhou, Jiangmen, Nanning, Zhangzhou, and Hangzhou) have return periods of less than two years, and the two island provinces of Hainan and Taiwan are visited by TCs the most. Guangdong, Guangxi, Fujian, and Zhejiang provinces in particular suffered severely from the destructive TCs.
      PubDate: Wed, 06 Jun 2018 07:12:16 +000
  • A Persistent Fog Event Involving Heavy Pollutants in Yancheng Area of
           Jiangsu Province

    • Abstract: In the early December 2013, dense fog involving heavy pollutants lasted for 9 days in the Yancheng area. The characteristics, formation, and lasting mechanisms of this persistent fog were analyzed based on observational data at the Sheyang site, reanalysis data, and final analysis data from NCEP/NCAR, combining with the weather background and meteorological and physical variable fields. Results include that (1) the fog process was characterized by long duration, low visibility, and high pollutants concentration, (2) the atmospheric general circulation contributed to the sustainability and development of the heavily polluted fog, (3) deep inversion was the key thermal factor causing the heavily polluted fog, (4) the fog exhibited obvious outbreaks with good visibility weather turned to severe fog several times, and (5) the weak cold air invasion and radiative cooling were the triggering factors to the sudden enhancement of the fog.
      PubDate: Tue, 05 Jun 2018 00:00:00 +000
  • Impact of Using Near Real-Time Green Vegetation Fraction in Noah Land
           Surface Model of NOAA NCEP on Numerical Weather Predictions

    • Abstract: Green vegetation fraction (GVF) is one of the input parameters of the Noah land surface model (LSM) that is the land component of a number of operational numerical weather prediction (NWP) models at the National Centers for Environmental Prediction (NCEP) of NOAA. The Noah LSM in current NCEP operational NWP models has been using static multiyear averages of monthly GVF derived from satellite observations of NOAA Advanced Very High Resolution Radiometer (AVHRR) normalized difference vegetation index. The multiyear averages of GVF are evidently not the representative of actual conditions of the land surface vegetation cover. This study used a near-real-time (NRT) GVF data set generated from the 8-day composite of the leaf area index product from the Moderate Resolution Imaging Spectroradiometer (MODIS) to assess the impact of NRT GVF on off-line Noah LSM simulations and NWP forecast model. Simulations of the off-line Noah LSM in the Land Information System (LIS) and weather forecasts of the NASA-Unified Weather and Research Forecasting (NUWRF) were obtained using either the static multiyear average AVHRR GVF data set or the NRT MODIS GVF while meteorological forcing data and other settings were kept the same. The off-line simulations and WRF forecasts were then compared against in situ measurements or reanalysis products to assess the impact of using NRT GVF. Improvements of both soil moisture simulations as well as forecasts of 2-meter air temperature and humidity and precipitation from NUWRF were observed using the NRT GVF data products. The RMSE in SM estimates from the off-line Noah model is reduced by around 1.0% (1.41%) during the green-up phase and by 1.48% (2.24%) over the senescence phase for the surface (root zone) SM simulations. Around 82.3% validation sites (out of 1178 sites) showed positive impact on coupled WRF model with the insertion of NRT GVF.
      PubDate: Tue, 05 Jun 2018 00:00:00 +000
  • Analysis of Wind Data, Calculation of Energy Yield Potential, and
           Micrositing Application with WAsP

    • Abstract: The parameters required for building a wind power plant have been calculated using the fuzzy logic method by means of Wind Atlas Analysis and Application Program (WAsP) in this study. Overall objectives of the program include analysis of raw data, evaluation of wind and climate, construction of a wind atlas, and estimation of wind power potential. With the analysis performed in the application, the average wind velocity, average power density, energy potential from micrositing, capacity factor, unit cost price, and period of redemption have been calculated, which are needed by the project developer during the decision-making stage and intended to be used as the input unit in the fuzzy logic-based system designed. It is aimed at processing the parameters calculated by the designed fuzzy logic-based decision-making system at the rule base and generating a compatibility factor that will allow for making the final decision in building wind power plants.
      PubDate: Wed, 30 May 2018 09:36:29 +000
  • Case Study of Ground-Based Glaciogenic Seeding of Clouds over the
           Pyeongchang Region

    • Abstract: Ground-based glaciogenic seeding experiments were conducted at the Daegwallyeong Cloud Physics Observation Site (CPOS) from 2012 to 2015 for the target area Yongpyeong, which lies 9 km away. The preseeding (NOSEED) and seeding (SEED) periods were defined based on the simulation results of AgI concentration (>10 L−1) in the Weather Research and Forecast (WRF) model with the modified Morrison scheme in microphysics. It was difficult to determine whether snow enhancement via seeding occurred over the entire target area due to uncertainties associated with limitations such as observations and numerical model based on only two points (seeding and target sites). However, in three of four cases, the vertical reflectivity from micro rain radar, total concentration, and average size of snow particles observed at PARSIVEL and precipitation increased in the seeding effect time. In two of four cases, the simulated increased precipitation during the seeding effect time was also observed. In one case that did not show changes after seeding, it is analyzed that a sufficient cloud depth was not supplied to the seeding region due to the blocking effect of the Taebaek Mountains.
      PubDate: Mon, 28 May 2018 09:57:06 +000
  • Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by
           Means of Alpha Model with Multisensor SAR Data

    • Abstract: The objective of this research is to optimize the Alpha approximation model for soil moisture retrieval using multitemporal SAR data. The Alpha model requires prior knowledge of soil moisture range to constrain soil moisture estimation. The solution of the Alpha model is an undetermined problem due to the fact that the number of observation equations is less than the number of unknown parameters. This research primarily focused on the optimization of Alpha model by employing multisensor and multitemporal SAR data. The disadvantage of the Alpha model can be eliminated by the combination of multisensor SAR data. The optimized Alpha model was evaluated on the basis of a comprehensive campaign for soil moisture retrieval, which acquired multisensor time series SAR data and coincident field measurements. The agreement between the estimated and measured soil moisture was within a root mean square error of 0.08 cm3/cm3 for both methods. The optimized Alpha model shows an obvious improvement for soil moisture retrieval. The results demonstrated that multisensor and multitemporal SAR data are favorable for time series soil moisture retrieval over bare agricultural areas.
      PubDate: Wed, 23 May 2018 08:47:34 +000
  • Sensitivity Study on the Influence of Parameterization Schemes in WRF_ARW
           Model on Short- and Medium-Range Precipitation Forecasts in the Central
           Andes of Peru

    • Abstract: A sensitivity study of the performance of the Weather Research and Forecasting regional model (WRF, version 3.7) to the use of different microphysics, cumulus, and boundary layer parameterizations for short- and medium-term precipitation forecast is conducted in the Central Andes of Peru. Lin-Purdué, Thompson, and Morrison microphysics schemes were tested, as well as the Grell–Freitas, Grell 3d, and Betts–Miller–Janjic cumulus parameterizations. The tested boundary layer schemes were the Yonsei University and Mellor–Yamada–Janjic. A control configuration was defined, using the Thompson, Grell–Freitas, and Yonsei University schemes, and a set of numerical experiments is made, using different combinations of parameterizations. Data from 19 local meteorological stations and regional and global gridded were used for verification. It was concluded that all the configurations overestimate precipitation, but the one using the Morrison microphysical scheme had the best performance, based on the indicators of bias () and root mean square error (RMSE). It is recommended not to use the Betts–Miller–Janjic scheme in this region for low resolution domains. Categorical forecast verification of the occurrence of rainfall as a binary variable showed detection rates higher than 85%. According to this criterion, the best performing configuration was the combination of Betts–Miller–Janjic and Morrison. Spatial verification showed that, even if all the configurations overestimated precipitation in some degree, spatial patterns of rainfall match the TRMM and PISCO rainfall data. Morrison’s microphysics scheme shows the best results, and consequently, this configuration is recommended for short- and medium-term rainfall forecasting tasks in the Central Andes of Peru and particularly in the Mantaro basin. The results of a special sensitivity experiment showed that the activation or not of cumulus parametrization for the domain of 3 km resolution is not relevant for the precipitation forecast in the study region.
      PubDate: Tue, 22 May 2018 10:43:10 +000
  • Corrigendum to “High-Resolution Monthly Precipitation Fields
           (1913–2015) over a Complex Mountain Area Centred on the Forni Valley
           (Central Italian Alps)”

    • PubDate: Tue, 22 May 2018 00:00:00 +000
  • Comparison of 3DVar and EnSRF Data Assimilation Using Radar Observations
           for the Analysis and Prediction of an MCS

    • Abstract: Using radar observations, the performances of the ensemble square root filter (EnSRF) and an indirect three-dimensional variational (3DVar) data assimilation method were compared for a mesoscale convective system (MCS) that occurred in the Front Range of the Rocky Mountains, Colorado (USA). The results showed that the root mean square innovations (RMSIs) of EnSRF were lower than 3DVar for radar reflectivity and radial velocity and that the spread of EnSRF was generally consistent with its RMSIs. EnSRF substantially improved the analysis of the MCS compared with an experiment without radar data assimilation, and it produced a slight but noticeable improvement over 3DVar in terms of both coverage and intensity. Forecast results initiated from the final analysis revealed that EnSRF generally produced the best prediction of the MCS, with improved quantitative reflectivity and precipitation forecast skills. EnSRF also demonstrated better performance than 3DVar in the prediction of neighborhood probability for reflectivity at thresholds of 20 and 35 dBZ, which better matched the observed radar reflectivity in terms of both shape and extension. Additionally, the humidity, temperature, and wind fields were also improved by EnSRF; the largest error reduction was found in the water vapor field near the surface and at upper levels.
      PubDate: Sun, 20 May 2018 07:26:41 +000
  • 3D Variable Coefficient KdV Equation and Atmospheric Dipole Blocking

    • Abstract: A (2 + 1)-dimensional variable coefficient Korteweg-de Vries (3D VCKdV) equation is first derived in this paper by means of introducing 2-dimensional space and time slow-varying variables and the multiple-level approximation method from the well-known barotropic and quasi-geostrophic potential vorticity equation without dissipation. The exact analytical solution of the 3D VCKdV equation is obtained successfully by making use of CK’s direct method and the standard Zakharov–Kuznetsov equation. By some arbitrary functions and the analytical solution, a dipole blocking evolution process with twelve days’ lifetime is described, and the result illustrates that the central axis of the dipole is no longer perpendicular to the vertical direction but has a certain angle to vertical direction. The comparisons with the previous researches and Urals dipole blocking event demonstrate that 3D VCKdV equation is more suitable for describing the complex atmospheric blocking phenomenon.
      PubDate: Thu, 17 May 2018 00:00:00 +000
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