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1
Milovidov, V. "To Origins of «Humanitarian Economy»." World Economy and International Relations, no. 7 (2013): 3–11. http://dx.doi.org/10.20542/0131-2227-2013-7-3-11.
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Problems of liberalism in business relationship were designated as early as in Ancient philosophy and culture. The author details the essence of Classical Greek philosophers and thinkers, Diogenes's of Synop and Hesiod's views of these subjects.
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Hintz, K. S., H. Vedel, E. Kaas, and N. W. Nielsen. "Estimation of Wind Speed and Roughness Length Using Smartphones: Method and Quality Assessment." Journal of Atmospheric and Oceanic Technology 37, no. 8 (August 1, 2020): 1319–32. http://dx.doi.org/10.1175/jtech-d-19-0037.1.
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AbstractCrowdsourced data are now seen as a potential source of high-resolution observations in the atmospheric sciences. In this paper we investigate a potential data source, wind observations obtained using anemometers connected to handheld smartphones. The aim of this paper is twofold: to assess the quality of raw and height-extrapolated wind measurements from the handheld anemometer against professional-grade surface synoptic observation (SYNOP) stations, and to use these data of opportunity to infer a more accurate estimation of terrain roughness lengths. Roughness lengths are essential in numerical weather prediction; however, they are often poorly determined. Roughness lengths are also necessary when correcting near-surface wind observations for height offsets. For the analysis we performed a series of field experiments measuring wind profiles using handheld anemometers at roughly 2 m above ground. These raw measurements were then extrapolated to 10-m height using roughness lengths from three different sources. The extrapolation enabled us to compare the quality of roughness lengths estimated from smartphone measurements with those from traditional sources, as well as to assess the quality of these wind measurements against the professional-grade stations. We find that the handheld wind measurements are comparable in quality to wind measurements from SYNOP stations at 10-m height and that for some cases the handheld measurements can be more representative than SYNOP stations only about a kilometer away. To determine the roughness lengths, we examine a method that is based on the turbulent intensity derived from the high-frequency signal of the smartphone wind measurements. Under certain circumstances, the roughness lengths obtained with the approach presented here are superior to traditional sources.
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Sokol, Z., and J. Štekl. "Dreidimensionale mesoskalige objektive Analyse der ausgewählten Elemente aus den SYNOP und SYRED Meldungen." Meteorologische Zeitschrift 3, no. 4 (September 2, 1994): 242–46. http://dx.doi.org/10.1127/metz/3/1994/242.
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Hynčica, Martin, and Radan Huth. "Long-term changes in precipitation phase in Czechia." Geografie 124, no. 1 (2019): 41–55. http://dx.doi.org/10.37040/geografie2019124010041.
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Long-term changes in precipitation phase are investigated at ten stations in Czechia. Trends are calculated from 1983 to 2018 for the period between November and April. Daily SYNOP reports and daily precipitation totals are used at every station, where number and occurrence of specific codes in SYNOP report determine daily precipitation totals as solid, combined (which represents, to a large extent, category of mixed precipitation), or liquid. Thereafter, it is possible to calculate trends of all precipitation phases as well as the proportion of solid to total precipitation (S/P; in %). The average S/P trend over all Czech stations is significantly negative (−0.60%·year-1) and accompanied by a sharp decrease in solid precipitation (−1.66 mm·year-1) and an increase in combined precipitation (1.50 mm·year-1). Thus, our results show a ship of precipitation phase from solid to combined. Because of the dependence of S/P on air temperature, we suppose that the current S/P decline is a manifestation of rising air temperatures in the past decades.
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Arbain, Ardhi Adhary. "KLIMATOLOGI BADAI PETIR DI WILAYAH JAKARTA DAN SEKITARNYA BERDASARKAN OBSERVASI SYNOP TAHUN 2000-2012." Jurnal Sains & Teknologi Modifikasi Cuaca 17, no. 1 (June 15, 2016): 1. http://dx.doi.org/10.29122/jstmc.v17i1.1175.
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IntisariKlimatologi badai petir (TS) dianalisis dengan memanfaatkan pengamatan SYNOP per 3-jam dari 8 stasiun cuaca BMKG yang berada di wilayah Jakarta dan sekitarnya selama periode tahun 2000-2012. Frekuensi kejadian TS pada tiap lokasi dihitung berdasarkan perbandingan antara jumlah laporan TS pada data SYNOP dengan jumlah total observasi yang dilakukan oleh stasiun yang bersangkutan. Hasil pengolahan data menunjukkan bahwa TS memiliki dua pola klimatologi yang dominan dan paling sering terjadi pada periode sebelum dan sesudah musim hujan, terutama pada bulan November dan April. Hasil analisis juga menunjukkan bahwa TS sangat bergantung pada topografi dari lokasi yang bersangkutan, yang mengindikasikan pengaruh kuat dari siklus harian akibat konveksi kuat dan pola angin darat-laut di wilayah Jakarta dan sekitarnya. Pada beberapa lokasi yang berdekatan dengan Teluk Jakarta, periode puncak kejadian TS juga terjadi pada puncak musim hujan akibat pengaruh dari monsun barat laut dan seruak dingin yang datang dari Laut Tiongkok Selatan. Variabilitas iklim global seperti ENSO (El Nino Southern Oscillation) dan MJO (Madden-Julian Oscillation) turut memberikan pengaruh signifikan terhadap frekuensi TS. Hasil analisis menunjukkan bahwa frekuensi TS mengalami peningkatan pada periode La Nina kuat, serta pada periode sebelum dan sesudah MJO melintasi Indonesia bagian barat. AbstractThunderstorm (TS) climatology was analyzed by utilizing 3-hourly SYNOP observation of 8 BMKG’s weather stations in Jakarta capital and surrounding area during the period of 2000-2012. The frequency of TS occurrences at each location was calculated based on the ratio of TS reports to the total number of SYNOP observations conducted by the stations. The results show that the TS has two dominant climatological patterns in which most cases, the peak periods both preced and succeed the rainy season, especially in November and April. The results also imply that TS occurences are heavily influenced by the topography at each location, which indicate the great dependency of TS to the diurnal cycle generated by strong convective activity and land-sea breeze circulation over Jakarta and surronding regions. On the other hand, the peak period of TS at some locations close to Jakarta Bay, occurs simultaneously with the peak of rainy season by the influence of north-westerly monsoon and cold surge coming from the South China Sea. Global climate variabilities such as ENSO (El Nino Southern Oscillation) and MJO (Madden-Julian Oscillation) also significantly contribute to the anomaly of TS frequency. The results show an enhancement of TS frequency during the period of strong La Nina, as well as the period before and after MJO passes the western part of Indonesia.
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Kämäräinen, Matti, Otto Hyvärinen, Kirsti Jylhä, Andrea Vajda, Simo Neiglick, Jaakko Nuottokari, and Hilppa Gregow. "A method to estimate freezing rain climatology from ERA-Interim reanalysis over Europe." Natural Hazards and Earth System Sciences 17, no. 2 (February 22, 2017): 243–59. http://dx.doi.org/10.5194/nhess-17-243-2017.
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Abstract. A method for estimating the occurrence of freezing rain (FZRA) in gridded atmospheric data sets was evaluated, calibrated against SYNOP weather station observations, and applied to the ERA-Interim reanalysis for climatological studies of the phenomenon. The algorithm, originally developed at the Finnish Meteorological Institute for detecting the precipitation type in numerical weather prediction, uses vertical profiles of relative humidity and temperature as input. Reanalysis data in 6 h time resolution were analysed over Europe for the period 1979–2014. Mean annual and monthly numbers of FZRA events, as well as probabilities of duration and spatial extent of events, were then derived. The algorithm was able to accurately reproduce the observed, spatially averaged interannual variability of FZRA (correlation 0.90) during the 36-year period, but at station level rather low validation and cross-validation statistics were achieved (mean correlation 0.38). Coarse-grid resolution of the reanalysis and misclassifications to other freezing phenomena in SYNOP observations, such as ice pellets and freezing drizzle, contribute to the low validation results at station level. Although the derived gridded climatology is preliminary, it may be useful, for example, in safety assessments of critical infrastructure.
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Porter, David L., Ella B. Dobson, and Scott M. Glenn. "Measurements of dynamic topography during synop utilizing a Geosat synthetic geoid." Geophysical Research Letters 19, no. 18 (September 23, 1992): 1847–50. http://dx.doi.org/10.1029/92gl01881.
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Lopez, Philippe. "Experimental 4D-Var Assimilation of SYNOP Rain Gauge Data at ECMWF." Monthly Weather Review 141, no. 5 (May 1, 2013): 1527–44. http://dx.doi.org/10.1175/mwr-d-12-00024.1.
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Abstract Four-dimensional variational data assimilation (4D-Var) experiments with 6-hourly rain gauge accumulations observed at synoptic stations (SYNOP) around the globe have been run over several months, both at high resolution in an ECMWF operations-like framework and at lower resolution with the reference observational coverage reduced to surface pressure data only, as would be expected in early twentieth-century periods. The key aspects of the technical implementation of rain gauge data assimilation in 4D-Var are described, which include the specification of observation errors, bias correction procedures, screening, and quality control. Results from experiments indicate that the positive impact of rain gauges on forecast scores remains limited in the operations-like context because of their competition with all other observations already available. In contrast, when only synoptic station surface pressure observations are assimilated in the data-poor control experiment, the additional assimilation of rain gauge measurements substantially improves not only surface precipitation scores, but also analysis and forecast scores of temperature, geopotential, wind, and humidity at most atmospheric levels and for forecast ranges up to 10 days. The verification against Meteosat infrared imagery also shows a slight improvement in the spatial distribution of clouds. This suggests that assimilating rain gauge data available during data-sparse periods of the past might help to improve the quality of future reanalyses and subsequent forecasts.
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Rohm, Witold, Jakub Guzikowski, Karina Wilgan, and Maciej Kryza. "4DVAR assimilation of GNSS zenith path delays and precipitable water into a numerical weather prediction model WRF." Atmospheric Measurement Techniques 12, no. 1 (January 18, 2019): 345–61. http://dx.doi.org/10.5194/amt-12-345-2019.
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Abstract. The GNSS data assimilation is currently widely discussed in the literature with respect to the various applications for meteorology and numerical weather models. Data assimilation combines atmospheric measurements with knowledge of atmospheric behavior as codified in computer models. With this approach, the “best” estimate of current conditions consistent with both information sources is produced. Some approaches also allow assimilating the non-prognostic variables, including remote sensing data from radar or GNSS (global navigation satellite system). These techniques are named variational data assimilation schemes and are based on a minimization of the cost function, which contains the differences between the model state (background) and the observations. The variational assimilation is the first choice for data assimilation in the weather forecast centers, however, current research is consequently looking into use of an iterative, filtering approach such as an extended Kalman filter (EKF). This paper shows the results of assimilation of the GNSS data into numerical weather prediction (NWP) model WRF (Weather Research and Forecasting). The WRF model offers two different variational approaches: 3DVAR and 4DVAR, both available through the WRF data assimilation (WRFDA) package. The WRFDA assimilation procedure was modified to correct for bias and observation errors. We assimilated the zenith total delay (ZTD), precipitable water (PW), radiosonde (RS) and surface synoptic observations (SYNOP) using a 4DVAR assimilation scheme. Three experiments have been performed: (1) assimilation of PW and ZTD for May and June 2013, (2) assimilation of PW alone; PW, with RS and SYNOP; ZTD alone; and finally ZTD, with RS and SYNOP for 5–23 May 2013, and (3) assimilation of PW or ZTD during severe weather events in June 2013. Once the initial conditions were established, the forecast was run for 24 h. The major conclusion of this study is that for all analyzed cases, there are two parameters significantly changed once GNSS data are assimilated in the WRF model using GPSPW operator and these are moisture fields and rain. The GNSS observations improves forecast in the first 24 h, with the strongest impact starting from a 9 h lead time. The relative humidity forecast in a vertical profile after assimilation of ZTD shows an over 20 % decrease of mean error starting from 2.5 km upward. Assimilation of PW alone does not bring such a spectacular improvement. However, combination of PW, SYNOP and radiosonde improves distribution of humidity in the vertical profile by maximum of 12 %. In the three analyzed severe weather cases PW always improved the rain forecast and ZTD always reduced the humidity field bias. Binary rain analysis shows that GNSS parameters have significant impact on the rain forecast in the class above 1 mm h−1.
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Laird, Neil, Ryan Sobash, and Natasha Hodas. "Climatological Conditions of Lake-Effect Precipitation Events Associated with the New York State Finger Lakes." Journal of Applied Meteorology and Climatology 49, no. 5 (May 1, 2010): 1052–62. http://dx.doi.org/10.1175/2010jamc2312.1.
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Abstract A climatological analysis was conducted of the environmental and atmospheric conditions that occurred during 125 identified lake-effect (LE) precipitation events in the New York State Finger Lakes region for the 11 winters (October–March) from 1995/96 through 2005/06. The results complement findings from an earlier study reporting on the frequency and temporal characteristics of Finger Lakes LE events that occurred as 1) isolated precipitation bands over and downwind of a lake (NYSFL events), 2) an enhancement of LE precipitation originating from Lake Ontario (LOenh events), 3) an LE precipitation band embedded within widespread synoptic precipitation (SYNOP events), or 4) a transition from one type to another. In comparison with SYNOP and LOenh events, NYSFL events developed with the 1) coldest temperatures, 2) largest lake–air temperature differences, 3) weakest wind speeds, 4) highest sea level pressure, and 5) lowest height of the stable-layer base. Several significant differences in conditions were found when only one or both of Cayuga and Seneca Lakes, the largest Finger Lakes, had LE precipitation as compared with when the smaller Finger Lakes also produced LE precipitation. In addition, transitional events containing an NYSFL time period occurred in association with significantly colder and drier air masses, larger lake–air temperature differences, and a less stable and shallower boundary layer in comparison with those associated with solitary NYSFL events.
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Bari, Driss. "A Preliminary Impact Study of Wind on Assimilation and Forecast Systems into the One-Dimensional Fog Forecasting Model COBEL-ISBA over Morocco." Atmosphere 10, no. 10 (October 11, 2019): 615. http://dx.doi.org/10.3390/atmos10100615.
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The assimilation impact of wind data from aircraft measurements (AMDAR), surface synoptic observations (SYNOP) and 3D numerical weather prediction (NWP) mesoscale model, on short-range numerical weather forecasting (up to 12 h) and on the assimilation system, using the one-dimensional fog forecasting model COBEL-ISBA (Code de Brouillard à l’Échelle Locale-Interactions Soil Biosphere Atmosphere), is studied in the present work. The wind data are extracted at Nouasseur airport, Casablanca, Morocco, over a winter period from the national meteorological database. It is the first time that wind profiles (up to 1300 m) are assimilated in the framework of a single-column model. The impact is assessed by performing NWP experiments with data denial tests, configured to be close to the operational settings. The assimilation system estimates the flow-dependent background covariances for each run of the model and takes the cross-correlations between temperature, humidity and wind components into account. When assimilated into COBEL-ISBA with an hourly update cycle, the wind field has a positive impact on temperature and specific humidity analysis and forecasts accuracy. Thus, a superior fit of the analysis background fields to observations is found when assimilating AMDAR without NWP wind data. The latter has shown a detrimental impact in all experiments. Besides, wind assimilation gave a clear improvement to short-range forecasts of near-surface thermodynamical parameters. Although, assimilation of SYNOP and AMDAR wind measurements slightly improves the probability of detection of fog but also increases the false alarms ratio by a lower magnitude.
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Bédard, Joël, Stéphane Laroche, and Pierre Gauthier. "Near-Surface Wind Observation Impact on Forecasts: Temporal Propagation of the Analysis Increment." Monthly Weather Review 145, no. 4 (April 1, 2017): 1549–64. http://dx.doi.org/10.1175/mwr-d-16-0310.1.
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Abstract This study examines the assimilation of near-surface wind observations over land to improve wind nowcasting and short-term tropospheric forecasts. A new geostatistical operator based on geophysical model output statistics (GMOS) is compared with a bilinear interpolation scheme (Bilin). The multivariate impact on forecasts and the temporal evolution of the analysis increments produced are examined as well as the influence of background error covariances on different components of the prediction system. Results show that Bilin significantly degrades surface and upper-air fields when assimilating only wind data from 4942 SYNOP stations. GMOS on the other hand produces smaller increments that are in better agreement with the model state. It leads to better short-term near-surface wind forecasts and does not deteriorate the upper-air forecasts. The information persists longer in the system with GMOS, although the local improvements do not propagate beyond 6-h lead time. Initial model tendencies indicate that the mass field is not significantly altered when using static error covariances and the boundary layer parameterizations damp the poorly balanced increment locally. Conversely, most of the analysis increment is propagated when using flow-dependent error statistics. It results in better balanced wind and mass fields and provides a more persistent impact on the forecasts. Forecast accuracy results from observing system experiments (assimilating SYNOP winds with all observations used operationally) are generally neutral. Nevertheless, forecasts and analyses from GMOS are more self-consistent than those from both Bilin and a control experiment (not assimilating near-surface winds over land) and the information from the observations persists up to 12-h lead time.
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Kirschenstein, Małgorzata, and Kamil Krasuski. "Integration the Meteorological Data for Monitoring the Troposphere Condition Over the Military Aerodrome in Dęblin." Journal of KONBiN 49, no. 3 (October 1, 2019): 115–35. http://dx.doi.org/10.2478/jok-2019-0053.
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Abstract The integration of meteorological and tropospheric data is extremely important in precise monitoring of the atmosphere condition over a selected aerodrome. The paper presents the results of troposphere monitoring over the military aerodrome EPDE in Dęblin in Lubelskie Voivodeship in Poland. The three sources of meteorological data were applied for troposphere monitoring, namely: GNSS satellite technique, SYNOP data, TAF data. The troposphere empirical models within the GNSS satellite technique were utilized in the designation of the meteorological parameters, e. g. temperature, pressure and relative humidity. In paper, the meteorological parameters were estimated using three deterministic model, e.g.: SA model, RTCA-MOPS model and also GPT model.
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Das, Razat Suvra, Sayedur Rahman Chowdhury, Milan Kumar Shiuli, and Shubha Sarker. "WEATHER PERTURBATIONS ASSOCIATED WITH THE TRANSIT OF TROPICAL CYCLONES IN THE COAST OF BANGLADESH." Earth Science Malaysia 4, no. 1 (February 27, 2020): 23–27. http://dx.doi.org/10.26480/esmy.01.2020.23.37.
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During the transition of tropical cyclone in the coast of Bangladesh, it is normally observed that there is a noticeable perturbation of weather parameters around the cyclone landfall zone. Through this research the extent of perturbation is assessed. To make the inventory 4 recent cyclones were selected that had made landfall in Bangladesh coast. They are cyclone MORA, cyclone ROANU, cyclone KOMEN and cyclone MAHASEN. Weather parameters selected to check their perturbation are wind speed, temperature, dew point temperature, atmospheric pressure, relative humidity and precipitation. The dispersion of these parameters from their normal state was measured also in accordance of their distance from the landfall area. To perform the task a time scale of 15 days was selected for each cyclone. Middle 3 days window were considered as most affected weather, 6 days prior and after the event were considered as normal (prevailing) weather. The Synop (observed) data was downloaded from the Ogimet.com. The data was then processed and decoded by Synop decoder and then further analyzed in MS Excel. In case of atmospheric pressure perturbation the highest perturbation was found 5.8 mb low on average than prevailing pressure up to 50 km from cyclone landfall. Wind speed perturbation was highest in 50 to 100 km area. Perturbation of temperature was highest in 0 to 50 km (about 2.1 °C low on average). Perturbation of dew point temperature was found negligible and humidity perturbation was found highest 6.63% high on average up to 50 km of landfall. In case of precipitation perturbation highest was found in 0 to 50 km area of landfall (38.76 mm high on average than prevailing weather), however precipitation perturbation was irregular beyond 100 km of landfall. The most perturbed weather parameter was found atmospheric pressure and the least affected was dew point temperature.
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Bendix, Jörg, Boris Thies, Jan Cermak, and Thomas Nauß. "Ground Fog Detection from Space Based on MODIS Daytime Data—A Feasibility Study." Weather and Forecasting 20, no. 6 (December 1, 2005): 989–1005. http://dx.doi.org/10.1175/waf886.1.
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Abstract The distinction made by satellite data between ground fog and low stratus is still an open problem. A proper detection scheme would need to make a determination between low stratus thickness and top height. Based on this information, stratus base height can be computed and compared with terrain height at a specific picture element. In the current paper, a procedure for making the distinction between ground fog and low-level stratus is proposed based on Moderate Resolution Imaging Spectroradiometer (MODIS, flying on board the NASA Terra and Aqua satellites) daytime data for Germany. Stratus thickness is alternatively derived from either empirical relationships or a newly developed retrieval scheme (lookup table approach), which relies on multiband albedo and radiative transfer calculations. A trispectral visible–near-infrared (VIS–NIR) approach has been proven to give the best results for the calculation of geometrical thickness. The comparison of horizontal visibility data from synoptic observing (SYNOP) stations of the German Weather Service and the results of the ground fog detection schemes reveals that the lookup table approach shows the best performance for both a valley fog situation and an extended layer of low stratus with complex local visibility structures. Even if the results are very encouraging [probability of detection (POD) = 0.76], relatively high percentage errors and false alarm ratios still occur. Uncertainties in the retrieval scheme are mostly due to possible collocation errors and known problems caused by comparing point and pixel data (time lag between satellite overpass and ground observation, etc.). A careful inspection of the pixels that mainly contribute to the false alarm ratio reveals problems with thin cirrus layers and the fog-edge position of the SYNOP stations. Validation results can be improved by removing these suspicious pixels (e.g., percentage error decreases from 28% to 22%).
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Dybbroe, Adam, Karl-Göran Karlsson, and Anke Thoss. "NWCSAF AVHRR Cloud Detection and Analysis Using Dynamic Thresholds and Radiative Transfer Modeling. Part II: Tuning and Validation." Journal of Applied Meteorology 44, no. 1 (January 1, 2005): 55–71. http://dx.doi.org/10.1175/jam-2189.1.
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Abstract Algorithms for cloud detection (cloud mask) and classification (cloud type) at high and midlatitudes using data from the Advanced Very High Resolution Radiometer (AVHRR) on board the current NOAA satellites and future polar Meteorological and Operational Weather Satellites (METOP) of the European Organisation for the Exploitation of Meteorological Satellites have been extensively validated over northern Europe and the adjacent seas. The algorithms have been described in detail in Part I and are based on a multispectral grouped threshold approach, making use of cloud-free radiative transfer model simulations. The thresholds applied in the algorithms have been validated and tuned using a database interactively built up over more than 1 yr of data from NOAA-12, -14, and -15 by experienced nephanalysts. The database contains almost 4000 rectangular (in the image data)-sized targets (typically with sides around 10 pixels), with satellite data collocated in time and space with atmospheric data from a short-range NWP forecast model, land cover characterization, elevation data, and a label identifying the given cloud or surface type as interpreted by the nephanalyst. For independent and objective validation, a large dataset of nearly 3 yr of collocated surface synoptic observation (Synop) reports, AVHRR data, and NWP model output over northern and central Europe have been collected. Furthermore, weather radar data were used to check the consistency of the cloud type. The cloud mask performs best over daytime sea and worst at twilight and night over land. As compared with Synop, the cloud cover is overestimated during night (except for completely overcast situations) and is underestimated at twilight. The algorithms have been compared with the more empirically based Swedish Meteorological and Hydrological Institute (SMHI) Cloud Analysis Model Using Digital AVHRR Data (SCANDIA), operationally run at SMHI since 1989, and results show that performance has improved significantly.
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Lestanto, Ardi Widi, and Jaka Anugrah Ivanda Paski. "UJI PERFORMA WRF DENGAN DATA ASIMILASI RADAR, SATELIT DAN SYNOP UNTUK PREDIKSI HUJAN DI JAKARTA." Jurnal Sains & Teknologi Modifikasi Cuaca 19, no. 1 (December 19, 2018): 1. http://dx.doi.org/10.29122/jstmc.v19i1.2818.
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Asimilasi data merupakan suatu metode estimasi yang diperoleh dari penggabungan antara output model NWP dan data-data pengukuran. Dalam beberapa tahun terakhir, model mesoscale resolusi tinggi diinisialisasi dengan menggunakan teknik data asimilasi (3DVAR/4DVAR) yang diterapkan untuk mempelajari fenomena meteorologi. Penelitian ini dilakukan di wilayah Jakarta dengan memanfaatkan data observasi sinoptik, data radiance satelit dan data radar Doppler C-Band EEC (Enterprise Electronics Corporation) di Jakarta. Penelitian ini menggunakan model numerik Weather Research and Forecasting (WRF) untuk menjalankan model tanpa asimilasi dan model dengan asimilasi data radar, satelit dan sinoptik menggunakan sistem 3DVAR. Analisis dilakukan secara kuantitatif untuk menguji performa model terhadap data observasi dan analisis spasial dengan mencari nilai selisih curah hujan dengan data GSMaP melalui metode overlay. Hasil membuktikan performa terbaik dari hasil prediksi distribusi hujan spasial adalah model asimilasi satelit kemudian model asimilasi radar dan terakhir model asimilasi synoptic. Uji performa melalui tabel kontingensi untuk mengetahui nilai PC, TS, FAR, dan POD. Model asimilasi satelit memiliki performa paling baik daripada model asimilasi lain. Untuk prediksi sesuai kategori hujan ringan model asimilasi satelit yang terbaik, sementara untuk kategori hujan sangat lebat model asimilasi synop adalah yang paling unggul.
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Kirschenstein, Małgorzata, and Kamil Krasuski. "Designation of the Troposphere Radio Refractivity for the Area of the Military Aerodrome in Dęblin." Journal of KONBiN 49, no. 3 (October 1, 2019): 137–58. http://dx.doi.org/10.2478/jok-2019-0054.
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Abstract The radio refractivity is one of major parameters in troposphere monitoring over a selected military aerodrome. The paper makes an in-depth analysis and description of the results of radio refractivity of the troposphere zone. The radio refractivity of the troposphere zone was estimated for the area of the military aerodrome EPDE in Dęblin, Poland. The radio refractivity of the troposphere zone was calculated using empirical troposphere models for the GNSS satellite technique as well as real meteorological data from the SYNOP message. In the paper, the authors demonstrate the results of wet, hydrostatic and total radio refractivity of the troposphere zone for EPDE military aerodrome. The SA and UNB3m models were applied in numerical computations of troposphere refractivity in an annual period.
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Werkmeister, A., M. Lockhoff, M. Schrempf, K. Tohsing, B. Liley, and G. Seckmeyer. "Comparing satellite- to ground-based automated and manual cloud coverage observations – a case study." Atmospheric Measurement Techniques 8, no. 5 (May 6, 2015): 2001–15. http://dx.doi.org/10.5194/amt-8-2001-2015.
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Abstract. In this case study we compare cloud fractional cover measured by radiometers on polar satellites (AVHRR) and on one geostationary satellite (SEVIRI) to ground-based manual (SYNOP) and automated observations by a cloud camera (Hemispherical Sky Imager, HSI). These observations took place in Hannover, Germany, and in Lauder, New Zealand, over time frames of 3 and 2 months, respectively. Daily mean comparisons between satellite derivations and the ground-based HSI found the deviation to be 6 ± 14% for AVHRR and 8 ± 16% for SEVIRI, which can be considered satisfactory. AVHRR's instantaneous differences are smaller (2 ± 22%) than instantaneous SEVIRI cloud fraction estimates (8 ± 29%) when compared to HSI due to resolution and scenery effect issues. All spaceborne observations show a very good skill in detecting completely overcast skies (cloud cover ≥ 6 oktas) with probabilities between 92 and 94% and false alarm rates between 21 and 29% for AVHRR and SEVIRI in Hannover, Germany. In the case of a clear sky (cloud cover lower than 3 oktas) we find good skill with detection probabilities between 72 and 76%. We find poor skill, however, whenever broken clouds occur (probability of detection is 32% for AVHRR and 12% for SEVIRI in Hannover, Germany). In order to better understand these discrepancies we analyze the influence of algorithm features on the satellite-based data. We find that the differences between SEVIRI and HSI cloud fractional cover (CFC) decrease (from a bias of 8 to almost 0%) with decreasing number of spatially averaged pixels and decreasing index which determines the cloud coverage in each "cloud-contaminated" pixel of the binary map. We conclude that window size and index need to be adjusted in order to improve instantaneous SEVIRI and AVHRR estimates. Due to its automated operation and its spatial, temporal and spectral resolution, we recommend as well that more automated ground-based instruments in the form of cloud cameras should be installed as they cover larger areas of the sky than other automated ground-based instruments. These cameras could be an essential supplement to SYNOP observation as they cover the same spectral wavelengths as the human eye.
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Balsamo, G., J.-F. Mahfouf, S. Bélair, and G. Deblonde. "A Land Data Assimilation System for Soil Moisture and Temperature: An Information Content Study." Journal of Hydrometeorology 8, no. 6 (December 1, 2007): 1225–42. http://dx.doi.org/10.1175/2007jhm819.1.
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Abstract A Canadian Land Data Assimilation System (CaLDAS) for the analysis of land surface prognostic variables is designed and implemented at the Meteorological Service of Canada for the initialization of numerical weather prediction and climate models. The assimilation of different data sources for the production of daily soil moisture and temperature analyses is investigated in a set of observing system simulation experiments over North America. A simplified variational technique is adapted to accommodate different observation types at their appropriate time in a 24-h time window. The screen-level observations of temperature and relative humidity, from conventional synoptic surface observations (SYNOP)/aviation routine weather report (METAR)/surface aviation observation (SA) reports, are considered together with presently available satellite observations provided by the Aqua satellite (microwave C-band), Geostationary Operational Environmental Satellite (GOES) [infrared (IR)], and observations available in the future by the Soil Moisture and Ocean Salinity (SMOS) satellite mission (microwave L-band). The aim of these experiments is to assess the information content brought by each observation type in the land surface analysis. The observation systems are simulated according to their spatial coverage, temporal availability, and nominal or expected errors. The results show that the observable with the largest dynamical response to perturbations of the control variable carries the greatest information content into the analysis. The observational error and the observation frequency counterbalance this feature in the analysis. If one considers a single observation both for soil moisture and soil temperature analysis, then satellite measurements (L-band, C-band, and IR in decreasing order of importance) are the primary source of information. When observation availability is considered and the highest temporal frequency of screen-level observations is used (1 h), a large amount of information is extracted from SYNOP-like reports. The screen-level observations are shown to provide valuable soil moisture information mainly during the daytime, while during nighttime these observations (and particularly screen-level temperature) are mostly useful for the soil temperature analysis. The results are presented with perspectives for future operational developments and preliminary assimilation experiments are performed with hourly screen-level observations.
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Laird, Neil F., Jared Desrochers, and Melissa Payer. "Climatology of Lake-Effect Precipitation Events over Lake Champlain." Journal of Applied Meteorology and Climatology 48, no. 2 (February 1, 2009): 232–50. http://dx.doi.org/10.1175/2008jamc1923.1.
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Abstract This study provides the first long-term climatological analysis of lake-effect precipitation events that developed in relation to a small lake (having a surface area of ≤1500 km2). The frequency and environmental conditions favorable for Lake Champlain lake-effect precipitation were examined for the nine winters (October–March) from 1997/98 through 2005/06. Weather Surveillance Radar-1988 Doppler (WSR-88D) data from Burlington, Vermont, were used to identify 67 lake-effect events. Events occurred as 1) well-defined, isolated lake-effect bands over and downwind of the lake, independent of larger-scale precipitating systems (LC events), 2) quasi-stationary lake-effect bands over the lake embedded within extensive regional precipitation from a synoptic weather system (SYNOP events), or 3) a transition from SYNOP and LC lake-effect precipitation. The LC events were found to occur under either a northerly or a southerly wind regime. An examination of the characteristics of these lake-effect events provides several unique findings that are useful for comparison with known lake-effect environments for larger lakes. January was the most active month with an average of nearly four lake-effect events per winter, and approximately one of every four LC events occurred with southerly winds. Event initiation and dissipation occurred on a diurnal time scale with an average duration of 12.1 h. In general, Lake Champlain lake-effect events 1) typically yielded snowfall, with surface air temperatures rarely above 0°C, 2) frequently had an overlake mesolow present with a sea level pressure departure of 3–5 hPa, 3) occurred in a very stable environment with a surface inversion frequently present outside the Lake Champlain Valley, and 4) averaged a surface lake–air temperature difference of 14.4°C and a lake–850-hPa temperature difference of 18.2°C. Lake Champlain lake-effect events occur within a limited range of wind and temperature conditions, thus providing events that are more sensitive to small changes in environmental conditions than are large-lake lake-effect events and offering a more responsive system for subsequent investigation of connections between mesoscale processes and climate variability.
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Doutreloup, Sébastien, Coraline Wyard, Charles Amory, Christoph Kittel, Michel Erpicum, and Xavier Fettweis. "Sensitivity to Convective Schemes on Precipitation Simulated by the Regional Climate Model MAR over Belgium (1987–2017)." Atmosphere 10, no. 1 (January 17, 2019): 34. http://dx.doi.org/10.3390/atmos10010034.
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The aim of this study is to assess the sensitivity of convective precipitation modelled by the regional climate model MAR (Modèle Atmosphérique Régional) over 1987–2017 to four newly implemented convective schemes: the Bechtold scheme coming from the MESO-NH regional model and the Betts-Miller-Janjić, Kain-Fritsch and modified Tiedtke schemes coming from the WRF regional model. MAR version 3.9 is used here at a resolution of 10 km over a domain covering Belgium using the ERA-Interim reanalysis as forcing. The simulated precipitation is compared against SYNOP and E-OBS gridded precipitation data. Trends in total and convective precipitation over 1987–2017 are discussed. None of the MAR experiments compares better with observations than the others and they all show the same trends in (extreme) precipitation. Over the period 1987–2017, MAR suggests a significant increase in the mean annual precipitation amount over the North Sea but a significant decrease over High Belgium.
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Zumstein, Jean. "Der Prozess Der Relecture in Der Johanneischen Literatur." New Testament Studies 42, no. 3 (July 1996): 394–411. http://dx.doi.org/10.1017/s0028688500020853.
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Die gegenwärtige Exegese nimmt mehrheitlich an, dass die johan-neische Literatur in ihrer kanonischen Form (Joh, 1 Joh, 2 Joh, 3 Joh) das Resultat eines langen Prozesses der Ausgestaltung darstellt, der sich im wesentlichen der Tatigkeit einer Schule verdankt. Diese Annahme wirft zwei Fragen auf: Wie hat die johanneische Schule die Traditionen, deren Verwalterin sie war, aufgenommen und weitergegeben? Und welcher hermeneutischer Verfahren hat sie sich bedient, um die verschiedenen Ausformun-gen dieser Traditionen zu interpretieren und zu aktualisieren? Im Sinne einer Arbeitshypothese schlagen wir vor, im Prozess der Relecture eines der wichtigsten Verfahren zu sehen, das die theo-logische Arbeit der johanneischen Schule auszeichnet. Dieser Prozess der Relecture ist keine Erfindung der johanneischen Kreise; er ist bereits sowohl im Alten Testament, insbesondere in den prophetischen Büchern,4 als auch in den paulinischen und synop-tischen Traditionen belegt. Das Ziel der folgenden Ausführungen besteht darin, die unterschiedlichen Aspekte dieser Arbeit der Relecture, die wir in der johanneischen Literatur und insbesondere im vierten Evangelium wahrnehmen, zu beschreiben.
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Jafariserajehlou, Soheila, Linlu Mei, Marco Vountas, Vladimir Rozanov, John P. Burrows, and Rainer Hollmann. "A cloud identification algorithm over the Arctic for use with AATSR–SLSTR measurements." Atmospheric Measurement Techniques 12, no. 2 (February 18, 2019): 1059–76. http://dx.doi.org/10.5194/amt-12-1059-2019.
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Abstract. The accurate identification of the presence of cloud in the ground scenes observed by remote-sensing satellites is an end in itself. The lack of knowledge of cloud at high latitudes increases the error and uncertainty in the evaluation and assessment of the changing impact of aerosol and cloud in a warming climate. A prerequisite for the accurate retrieval of aerosol optical thickness (AOT) is the knowledge of the presence of cloud in a ground scene. In our study, observations of the upwelling radiance in the visible (VIS), near infrared (NIR), shortwave infrared (SWIR) and the thermal infrared (TIR), coupled with solar extraterrestrial irradiance, are used to determine the reflectance. We have developed a new cloud identification algorithm for application to the reflectance observations of the Advanced Along-Track Scanning Radiometer (AATSR) on European Space Agency (ESA)-Envisat and Sea and Land Surface Temperature Radiometer (SLSTR) on board the ESA Copernicus Sentinel-3A and -3B. The resultant AATSR–SLSTR cloud identification algorithm (ASCIA) addresses the requirements for the study AOT at high latitudes and utilizes time-series measurements. It is assumed that cloud-free surfaces have unchanged or little changed patterns for a given sampling period, whereas cloudy or partly cloudy scenes show much higher variability in space and time. In this method, the Pearson correlation coefficient (PCC) parameter is used to measure the “stability” of the atmosphere–surface system observed by satellites. The cloud-free surface is classified by analysing the PCC values on the block scale 25×25 km2. Subsequently, the reflection at 3.7 µm is used for accurate cloud identification at scene level: with areas of either 1×1 or 0.5×0.5 km2. The ASCIA data product has been validated by comparison with independent observations, e.g. surface synoptic observations (SYNOP), the data from AErosol RObotic NETwork (AERONET) and the following satellite products: (i) the ESA standard cloud product from AATSR L2 nadir cloud flag; (ii) the product from a method based on a clear-snow spectral shape developed at IUP Bremen (Istomina et al., 2010), which we call ISTO; and (iii) the Moderate Resolution Imaging Spectroradiometer (MODIS) products. In comparison to ground-based SYNOP measurements, we achieved a promising agreement better than 95 % and 83 % within ±2 and ±1 okta respectively. In general, ASCIA shows an improved performance in comparison to other algorithms applied to AATSR measurements for the identification of clouds in a ground scene observed at high latitudes.
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Przeździecki, Karol, and Jarosław Zawadzki. "Modification of the Land Surface Temperature – Vegetation Index Triangle Method for soil moisture condition estimation by using SYNOP reports." Ecological Indicators 119 (December 2020): 106823. http://dx.doi.org/10.1016/j.ecolind.2020.106823.
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Kotarba, Andrzej Z. "Inconsistency of surface-based (SYNOP) and satellite-based (MODIS) cloud amount estimations due to the interpretation of cloud detection results." International Journal of Climatology 37, no. 11 (February 20, 2017): 4092–104. http://dx.doi.org/10.1002/joc.5011.
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Calmanti, S., A. Dell’Aquila, F. Maimone, and V. Pelino. "Evaluation of climate patterns in a regional climate model over Italy using long-term records from SYNOP weather stations and cluster analysis." Climate Research 62, no. 3 (February 5, 2015): 173–88. http://dx.doi.org/10.3354/cr01256.
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Kunz, M. "The skill of convective parameters and indices to predict isolated and severe thunderstorms." Natural Hazards and Earth System Sciences 7, no. 2 (May 3, 2007): 327–42. http://dx.doi.org/10.5194/nhess-7-327-2007.
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Abstract. The preconvective environment on days with ordinary, widespread, and severe thunderstorms in Southwest Germany was investigated. Various thermodynamic and kinetic parameters calculated from radiosoundings at 12:00 UTC were verified against subsequent thunderstorm observations derived from SYNOP station data, radar data, and damage reports of a building insurance company. The skill of the convective parameters and indices to predict thunderstorms was evaluated by means of probability distribution functions, probabilities of thunderstorms according to an index threshold, and skill scores like the Heidke Skill Score (HSS) that are based on categorical verification. For the ordinary decision as to whether a thunderstorm day was expected or not, the best results were obtained with the original Lifted Index (80% prediction probability for LI≤−1.73; HSS=0.57 for LI≤1.76), the Showalter Index, and the modified K-Index. Considering days with isolated compared to widespread thunderstorms, the best performance is reached by the Deep Convective Index. For days with severe thunderstorms that caused damage due to hail, local storms or floods, the best prediction skill is found again for the Lifted Index and the Deep Convective Index, but also for the Potential Instability Index, the Delta-θe Index, and a version of the CAPE, where the lifting profile is determined by averaging over the lowest 100 hPa.
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Zhang, Xiaoyan, Hongli Wang, Xiang-Yu Huang, Feng Gao, and Neil A. Jacobs. "Using Adjoint-Based Forecast Sensitivity Method to Evaluate TAMDAR Data Impacts on Regional Forecasts." Advances in Meteorology 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/427616.
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This study evaluates the impact of Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observations on regional 24-hour forecast error reduction over the Continental United States (CONUS) domain using adjoint-based forecast sensitivity to observation (FSO) method as the diagnostic tool. The relative impact of TAMDAR observations on reducing the forecast error was assessed by conducting the WRFDA FSO experiments for two two-week-long periods, one in January and one in June 2010. These experiments assimilated operational TAMDAR data and other conventional observations, as well as GPS refractivity (GPSREF). FSO results show that rawinsonde soundings (SOUND) and TAMDAR exhibit the largest observation impact on 24 h WRF forecast, followed by GeoAMV, aviation routine weather reports (METAR), GPSREF, and synoptic observations (SYNOP). At 0000 and 1200 UTC, TAMDAR has an equivalent impact to SOUND in reducing the 24-hour forecast error. However, at 1800 UTC, TAMDAR has a distinct advantage over SOUND, which has the sparse observation report at these times. In addition, TAMDAR humidity observations at lower levels of the atmosphere (700 and 850 hPa) have a significant impact on 24 h forecast error reductions. TAMDAR and SOUND observations present a qualitatively similar observation impact between FSO and Observation System Experiments (OSEs).
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Tiriolo, Luca, Rosa Claudia Torcasio, Stefania Montesanti, and Stefano Federico. "Verification of a Real Time Weather Forecasting System in Southern Italy." Advances in Meteorology 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/758250.
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This paper shows the performance of an operational forecasting system, based on the regional atmospheric modeling system (RAMS), at 3 km horizontal resolution over southern Italy. The model is initialized from the 12 UTC operational analysis/forecasting cycle of the European Centre for Medium range Weather Forecasts (ECMWF). The forecast is issued for the following three days. The performance is evaluated for a whole year for the surface parameters: temperature, relative humidity, wind speed and direction, and precipitation. The verification has been performed against SYNOP stations over southern Italy. A dense non-GTS network over Calabria is used for precipitation. Results show that RMSE is about 2-3 K for temperature, 12–16% for relative humidity, 2.0–2.8 m/s for wind speed, and 55–75° for wind direction, the performance varying with the season and with the forecasting time. The error increases between the first and third forecast days. The verification of the rainfall forecast shows that the model underestimates the area of the precipitation. The model output statistics (MOS) is applied to all parameters but precipitation. Results show that the MOS reduces the RMSE by 0–30%, depending on the forecasting time, on the season and on the meteorological parameter.
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Perler, Donat, and Oliver Marchand. "A Study in Weather Model Output Postprocessing: Using the Boosting Method for Thunderstorm Detection." Weather and Forecasting 24, no. 1 (February 1, 2009): 211–22. http://dx.doi.org/10.1175/2008waf2007047.1.
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Abstract In this work, a new approach to weather model output postprocessing is presented. The adaptive boosting algorithm is used to train a set of simple base classifiers with historical data from weather model output, surface synoptic observation (SYNOP) messages, and lightning data. The resulting overall method then can be used to classify weather model output to identify potential thunderstorms. The method generates a certainty measure between −1 and 1, describing how likely a thunderstorm is to occur. Using a threshold, the measure can be converted to a binary decision. When compared to a linear discriminant and a method currently employed in an expert system from the German Weather Service, boosting achieves the best validation scores. A substantial improvement of the probability of detection of up to 72% and a decrease of the false alarm rate down to 34% can be achieved for the identification of thunderstorms in model analysis. Independent of the verification results, the method has several useful properties: good cross-validation results, short learning time (≤10 min sequential run time for the experiments on a standard PC), comprehensible inner values of the underlying statistical analysis, and the simplicity of adding predictors to a running system. This paper concludes with a set of possible other applications and extensions to the presented example of thunderstorm detection.
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Cowie, S. M., P. Knippertz, and J. H. Marsham. "A climatology of dust emission events from northern Africa using long-term surface observations." Atmospheric Chemistry and Physics Discussions 14, no. 6 (March 18, 2014): 7425–68. http://dx.doi.org/10.5194/acpd-14-7425-2014.
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Abstract. Long-term (1984–2012) surface observations from 70 stations in the Sahara and Sahel are used to explore the diurnal, seasonal and geographical variations in dust emission events and thresholds. The frequency of dust emission (FDE) is calculated using the present weather codes of SYNOP reports. Thresholds are estimated as the wind speed for which there is a 50% probability of dust emission and are then used to calculate strong wind frequency (SWF) and dust uplift potential (DUP), where the latter is an estimate of the dust-generating power of winds. Stations are grouped into six coherent geographical areas for more in-depth analysis. FDE is highest at stations in Sudan and overall peaks in spring north of 23° N. South of this, where stations are directly influenced by the summer monsoon, the annual cycle in FDE is more variable. Thresholds are highest in northern Algeria, lowest in the latitude band 16–21° N and have greatest seasonal variations in the Sahel. Spatial variability in thresholds partly explain spatial variability in frequency of dust emission events on an annual basis. However, seasonal variations in thresholds for the six grouped areas are not the main control on seasonal variations in FDE. This is demonstrated by highly correlated seasonal cycles of FDE and SWF which are not significantly changed by using a fixed, or seasonally varying, threshold. The likely meteorological mechanisms generating these patterns such as low-level jets and haboobs are discussed.
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Cowie, S. M., P. Knippertz, and J. H. Marsham. "A climatology of dust emission events from northern Africa using long-term surface observations." Atmospheric Chemistry and Physics 14, no. 16 (August 25, 2014): 8579–97. http://dx.doi.org/10.5194/acp-14-8579-2014.
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Abstract. Long-term (1984–2012) surface observations from 70 stations in the Sahara and Sahel are used to explore the diurnal, seasonal and geographical variations in dust emission events and thresholds. The frequency of dust emission (FDE) is calculated using the present weather codes of SYNOP reports. Thresholds are estimated as the wind speed for which there is a 50% probability of dust emission and are then used to calculate strong wind frequency (SWF) and dust uplift potential (DUP), where the latter is an estimate of the dust-generating power of winds. Stations are grouped into six coherent geographical areas for more in-depth analysis. FDE is highest at stations in Sudan and overall peaks in spring north of 23° N. South of this, where stations are directly influenced by the summer monsoon, the annual cycle in FDE is more variable. Thresholds are highest in northern Algeria, lowest in the latitude band 16–21° N and have greatest seasonal variations in the Sahel. Spatial variability in thresholds partly explain spatial variability in frequency of dust emission events on an annual basis. However, seasonal variations in thresholds for the six grouped areas are not the main control on seasonal variations in FDE. This is demonstrated by highly correlated seasonal cycles of FDE and SWF which are not significantly changed by using a fixed, or seasonally varying, threshold. The likely meteorological mechanisms generating these patterns such as low-level jets and haboobs are discussed.
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Meinen, Christopher S. "Accuracy in Mooring Motion Temperature Corrections." Journal of Atmospheric and Oceanic Technology 25, no. 12 (December 1, 2008): 2293–303. http://dx.doi.org/10.1175/2008jtecho555.1.
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Abstract Moored temperature sensors, whether fixed or profiling, routinely need to be corrected to remove the signals associated with the vertical motion of the sensors when the moorings “blow over” in strong flow events (for profiling sensors the problems occur only at the upper end of the profiling range). Hydrographic data are used to estimate the accuracy with which moored temperature sensors in the Gulf Stream can be corrected for mooring motion aliasing using standard correction techniques, and the implications for other ocean regions are discussed. Comparison with hydrographic data and coincident inverted echo sounder (IES) data from the Synoptic Ocean Prediction Experiment (SYNOP) shows that the errors inherent in mooring motion corrected temperatures during significant pressure deflections are potentially 2–3 times as large as previous estimates based on a smaller dataset of observations in the Kuroshio at approximately the same latitude in the Pacific. For sensors with a nominal level of 400 dbar and a typical root-mean-square pressure deflection of 150 dbar, accuracy limits of up to 0.7°C on the “corrected” temperatures are applicable. Deeper sensors typically have smaller accuracy bounds. There is a suggestion that the presence of a mode water layer near the nominal depth of the shallowest sensor can result in much higher errors in mooring motion corrected temperature data. The accuracy estimates derived herein should apply not only to moorings deployed in the Gulf Stream but also to all currents that exhibit similar velocity amplitudes and thermal gradients such as the Agulhas or Kuroshio.
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van der Plas, Emiel, Maurice Schmeits, Nicolien Hooijman, and Kees Kok. "A Comparative Verification of High-Resolution Precipitation Forecasts Using Model Output Statistics." Monthly Weather Review 145, no. 10 (October 2017): 4037–54. http://dx.doi.org/10.1175/mwr-d-16-0256.1.
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Verification of localized events such as precipitation has become even more challenging with the advent of high-resolution mesoscale numerical weather prediction (NWP). The realism of a forecast suggests that it should compare well against precipitation radar imagery with similar resolution, both spatially and temporally. Spatial verification methods solve some of the representativity issues that point verification gives rise to. In this paper, a verification strategy based on model output statistics (MOS) is applied that aims to address both double-penalty and resolution effects that are inherent to comparisons of NWP models with different resolutions. Using predictors based on spatial precipitation patterns around a set of stations, an extended logistic regression (ELR) equation is deduced, leading to a probability forecast distribution of precipitation for each NWP model, analysis, and lead time. The ELR equations are derived for predictands based on areal-calibrated radar precipitation and SYNOP observations. The aim is to extract maximum information from a series of precipitation forecasts, like a trained forecaster would. The method is applied to the nonhydrostatic model Harmonie-AROME (2.5-km resolution), HIRLAM (11-km resolution), and the ECMWF model (16-km resolution), overall yielding similar Brier skill scores for the three postprocessed models, but somewhat larger differences for individual lead times. In addition, the fractions skill score is computed using the three deterministic forecasts, showing slightly higher skill for the Harmonie-AROME model. In other words, despite the realism of Harmonie-AROME precipitation forecasts, they only perform similarly or somewhat better than precipitation forecasts from the two lower-resolution models, at least in the Netherlands.
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Giunta, G., R. Salerno, A. Ceppi, G. Ercolani, and M. Mancini. "Effects of Model Horizontal Grid Resolution on Short- and Medium-Term Daily Temperature Forecasts for Energy Consumption Application in European Cities." Advances in Meteorology 2019 (May 8, 2019): 1–12. http://dx.doi.org/10.1155/2019/1561697.
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A short-term forecast of energy consumption is affected by different factors related to the demand in residential, commercial, thermoelectric, and industrial sectors. This demand can be strongly constrained by weather variables, especially temperatures, whose forecast may be very useful to predict the balances between supply and demand, minimizing the risk of price volatility. Energy companies use the relationship between meteorological forecast output and energy request to provide an effective scheduling of national gas and power grids and reduce operational costs in critical periods. This work reports a comparison analysis for short- and medium-term daily temperature forecasts during the period 2013-2014 by using the weather model e-kmf™ (eni-kassandra meteo forecast), currently adopted in gas and power applications where meteorological output has a key role. This weather forecast system uses different models and initial data to develop probabilistic predictions from a perspective of eleven days ahead. In particular, a set of model runs with horizontal grid spacing of 5.5, 8, 13, and 18 km with the same domain size are undertaken to assess the sensitivity of temperature to horizontal resolutions. A nonlinear Kalman filter has been also applied to postprocess forecasted data in eight European cities (Milano, Roma, Torino, Napoli, Munich, Paris, Brussels, and London). Filtered forecasts over these cities have been compared to local observations taken from SYNOP (surface synoptic observations) and METAR (meteorological Aerodrome Report) stations. Skill scores of performance have been used to generally assess the forecast reliability up to day +11. In order to understand the sensitivity to the horizontal resolution, investigations have been carried out even during four specific periods of two weeks with stable and unstable weather conditions.
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Baldridge, W. Scott, Gregory L. Cole, Bruce A. Robinson, and George R. Jiracek. "Application of time-domain airborne electromagnetic induction to hydrogeologic investigations on the Pajarito Plateau, New Mexico, USA." GEOPHYSICS 72, no. 2 (March 2007): B31—B45. http://dx.doi.org/10.1190/1.2437701.
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We conducted a time-domain airborne electromagnetic (AEM) survey of part of the semiarid Pajarito Plateau of northern New Mexico to determine depths and lateral extent of perched aquifers in the vadose zone and depths and pathways of infiltration to the regional aquifer. The electrical resistivity of the plateau ranged over three orders of magnitude ([Formula: see text] to [Formula: see text]) to a depth of at least [Formula: see text]. Borehole and surface-derived data allow the correlation of resistivity images with the hydrogeology of the plateau. As expected, water exerts a significant control on resistivity. However, the presence of large amounts (up to 90%) of clay in some units, in conjunction with water, also has a significant effect, lowering resistivity (to [Formula: see text]) more than the presence of clay-free saturated zones alone. Because of the resulting low resistivity, we are able to better delineate a large,known volume of clay-altered volcaniclastic rock and postulate the presence of another. Resistivity values of [Formula: see text] cor-relate with depths to saturated zones where no clay is present, but they do not allow us to distinguish between one large or several smaller perched groundwater zones and the underlying regional zone of saturation. We imaged a region of significant infiltration related to a sewage treatment plant and to near-surface hydrogeo-logic conditions conducive to infiltration and correlated with a region of preferential transport of anthropogenic chemicals through the vadose zone. AEM data provide an important synop-tic view of the shallow (few hundred meters) resistivity structure of the plateau. Although interpretation of the data is not unique, when combined with borehole geologic, hydrologic, and geo-chemical data, it can provide relative depths to saturated zones, delineate regions of high clay content (zones of alteration), and image regions of recharge to the regional aquifer.
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Jung, Byoung-Joo, Hyun Mee Kim, Thomas Auligné, Xin Zhang, Xiaoyan Zhang, and Xiang-Yu Huang. "Adjoint-Derived Observation Impact Using WRF in the Western North Pacific." Monthly Weather Review 141, no. 11 (October 25, 2013): 4080–97. http://dx.doi.org/10.1175/mwr-d-12-00197.1.
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Abstract An increasing number of observations have contributed to the performance of numerical weather prediction systems. Accordingly, it is important to evaluate the impact of these observations on forecast accuracy. While the observing system experiment (OSE) requires considerable computational resources, the adjoint-derived method can evaluate the impact of all observational components at a lower cost. In this study, the effect of observations on forecasts is evaluated by the adjoint-derived method using the Weather Research and Forecasting Model, its adjoint model, and a corresponding three-dimensional variational data assimilation system in East Asia and the western North Pacific for the 2008 typhoon season. Radiance observations had the greatest total impact on forecasts, but conventional wind observations had the greatest impact per observation. For each observation type, the total impact was greatest for radiosonde and each Advanced Microwave Sounding Unit (AMSU)-A satellite, followed by surface synoptic observation from a land station (SYNOP), Quick Scatterometer (QuikSCAT), atmospheric motion vector (AMV) wind from a geostationary satellite (GEOAMV), and aviation routine weather reports (METARs). The fraction of beneficial observations was approximately 60%–70%, which is higher than that reported in previous studies. For several analyses of Typhoons Sinlaku (200813) and Jangmi (200815), dropsonde soundings taken near the typhoon had similar or greater observation impacts than routine radiosonde soundings. The sensitivity to the error covariance parameter indicates that reducing (increasing) observation (background) error covariance helps to reduce forecast error in the current analysis framework. The observation impact from OSEs is qualitatively similar to that from the adjoint method for major observation types. This study confirms that radiosonde observations provide primary information on the atmospheric state as in situ observations and that satellite radiances are an essential component of atmospheric observation systems.
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Min, Jing, Shuichi Okada, Makoto Kanzaki, Jeffrey S. Elmendorf, Kenneth J. Coker, Brian P. Ceresa, Li-Jyun Syu, Yoichi Noda, Alan R. Saltiel, and Jeffrey E. Pessin. "Synip." Molecular Cell 3, no. 6 (June 1999): 751–60. http://dx.doi.org/10.1016/s1097-2765(01)80007-1.
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Brinckmann, Sven, Stefan Krähenmann, and Peter Bissolli. "High-resolution daily gridded data sets of air temperature and wind speed for Europe." Earth System Science Data 8, no. 2 (October 14, 2016): 491–516. http://dx.doi.org/10.5194/essd-8-491-2016.
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Abstract. New high-resolution data sets for near-surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001–2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are SYNOP observations, partly supplemented by station data from the ECA&D data set (http://www.ecad.eu). These data are quality tested to eliminate erroneous data. By spatial interpolation of these station observations, grid data in a resolution of 0.044° (≈ 5km) on a rotated grid with virtual North Pole at 39.25° N, 162° W are derived. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al.(2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are used for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA-Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Variance explained by the regression ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1–2 K and 1–1.5 ms−1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The data sets presented in this article are published at doi:10.5676/DWD_CDC/DECREG0110v2.
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Brinckmann, S., S. Krähenmann, and P. Bissolli. "High-resolution daily gridded datasets of air temperature and wind speed for Europe." Earth System Science Data Discussions 8, no. 2 (August 12, 2015): 649–702. http://dx.doi.org/10.5194/essdd-8-649-2015.
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Abstract. New high-resolution datasets for near surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001–2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are hourly SYNOP observations, partly supplemented by station data from the ECA&D dataset (http://www.ecad.eu). These data are quality tested to eliminate erroneous data and various kinds of inhomogeneities. Grids in a resolution of 0.044° (5 km) are derived by spatial interpolation of these station data into the CORDEX area. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al. (2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are chosen for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Explained variance ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1–2 °C and 1–1.5 m s−1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The datasets presented in this article are published at http://dx.doi.org/10.5676/DWD_CDC/DECREG0110v1.
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van der Heij, Dirk G. "Synopsis publishing for improving the accessibility of 'grey' scholarly information." Journal of Information Science 11, no. 3 (September 1985): 95–107. http://dx.doi.org/10.1177/016555158501100301.
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In the 1970s, synopsis publishing was one of the topics raised in discussions on the future of primary communication. Tradi tional publishing practices were widely felt to be inefficient for users and producers alike. Since economic constraints were the main incentive for most synopsis publishing experiments, inter est in this idea faded away when journal publishers no longer felt that their journals' future was jeopardized, though author resistance was the main cause of the early discontinuation of many of these experiments. In this paper a plea is made for the virtues of synopsis publishing, not only as an economic necess ity but also for fundamental reasons, for the possibility it gives to separate physically the access, dissemination and archival functions of primary journals. Several attempts have been, and are being, made to improve the accessibility and availability of 'grey' scholarly literature, a large proportion of the world's scientific literature. Thus paper discusses some of these attempts and suggests that the dissemi nation function could be improved by bridging the gap between the bibliographic information in databases and the full docu ments in depositories. Most experiments in synopsis publishing so far have been based on full papers used as back-up for the synopses; the full papers were either published in mini- or microform, or made available on request. Grey literature as back-up to synopses has hardly been discussed in the literature, and the only standard on synopsis publishing issued so far treats this possibility only in an aside. This paper discusses the applicability of the synop sis publishing principle to grey reports and concludes that such ventures are likely to meet less disapproval and resistance from authors and other parties involved than are article-based sys tems. In 1984, Pudoc established the Netherlands Agricultural Report Depository (NARD), a venture in synopsis publishing based on Dutch unpublished reports in agriculture and (ap plied) biology. NARD's approach, procedures and early results are briefly discussed.
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Hebblethwaite, Peter. "That Synod." New Blackfriars 68, no. 811 (December 1987): 544–51. http://dx.doi.org/10.1111/j.1741-2005.1987.tb01293.x.
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Jeanneret, Fanny, Giovanni Martucci, Simon Pinnock, and Alexis Berne. "Correction of CCI cloud data over the Swiss Alps using ground-based radiation measurements." Atmospheric Measurement Techniques 11, no. 7 (July 17, 2018): 4153–70. http://dx.doi.org/10.5194/amt-11-4153-2018.
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Abstract. The validation of long-term cloud data sets retrieved from satellites is challenging due to their worldwide coverage going back as far as the 1980s. A trustworthy reference cannot be found easily at every location and every time. Mountainous regions present a particular problem since ground-based measurements are sparse. Moreover, as retrievals from passive satellite radiometers are difficult in winter due to the presence of snow on the ground, it is particularly important to develop new ways to evaluate and to correct satellite data sets over elevated areas. In winter for ground levels above 1000 m (a.s.l.) in Switzerland, the cloud occurrence of the newly released cloud property data sets of the ESA Climate Change Initiative Cloud_cci Project (Advanced Very High Resolution Radiometer afternoon series (AVHRR-PM) and Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua series) is 132 to 217 % that of surface synoptic (SYNOP) observations, corresponding to a rate of false cloud detections between 24 and 54 %. Furthermore, the overestimations increase with the altitude of the sites and are associated with particular retrieved cloud properties. In this study, a novel post-processing approach is proposed to reduce the amount of false cloud detections in the satellite data sets. A combination of ground-based downwelling longwave and shortwave radiation and temperature measurements is used to provide independent validation of the cloud cover over 41 locations in Switzerland. An agreement of 85 % is obtained when the cloud cover is compared to surface synoptic observations (90 % within ± 1 okta difference). The validation data are then co-located with the satellite observations, and a decision tree model is trained to automatically detect the overestimations in the satellite cloud masks. Cross-validated results show that 62±13 % of these overestimations can be identified by the model, reducing the systematic error in the satellite data sets from 14.4±15.5 % to 4.3±2.8 %. The amount of errors is lower, and, importantly, their distribution is more homogeneous as well. These corrections happen at the cost of a global increase of 7±2 % of missed clouds. Using this model, it is possible to significantly improve the cloud detection reliability in elevated areas in the Cloud_cci AVHRR-PM and MODIS-Aqua products.
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Musial, J. P., F. Hüsler, M. Sütterlin, C. Neuhaus, and S. Wunderle. "Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery." Atmospheric Measurement Techniques 7, no. 3 (March 28, 2014): 799–822. http://dx.doi.org/10.5194/amt-7-799-2014.
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Abstract. Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.
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Musial, J. P., F. Hüsler, M. Sütterlin, C. Neuhaus, and S. Wunderle. "Probabilistic approach to cloud and snow detection on AVHRR imagery." Atmospheric Measurement Techniques Discussions 6, no. 5 (September 25, 2013): 8445–507. http://dx.doi.org/10.5194/amtd-6-8445-2013.
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Abstract. The derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. The information about a confidence level of provided physical quantities is required to construct an error budget of higher level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data the common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher level products and may alter their usability. Within this scope a novel Probabilistic Cloud Mask (PCM) algorithm suited for the 1×1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on a decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve the probability estimates from the pre-computed Look Up Tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of thresholds. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the Invariant Coordinate System (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the PPSv2012 and MOD35 collection 6 cloud masks, SYNOP weather reports, CALIPSO vertical feature mask version 3 and to MOD10A1 collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with comparable or better results than the reference PPS algorithm.
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Ning, Liang, Hani Y. Suleiman, and Jeffrey H. Miner. "Synaptopodin Is Dispensable for Normal Podocyte Homeostasis but Is Protective in the Context of Acute Podocyte Injury." Journal of the American Society of Nephrology 31, no. 12 (September 16, 2020): 2815–32. http://dx.doi.org/10.1681/asn.2020050572.
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BackgroundSynaptopodin (Synpo) is an actin-associated protein in podocytes and dendritic spines. Many functions in regulating the actin cytoskeleton via RhoA and other pathways have been ascribed to Synpo, yet no pathogenic mutations in the SYNPO gene have been discovered in patients. Naturally occurring Synpo isoforms are known (Synpo-short and -long), and a novel truncated version (Synpo-T) is upregulated in podocytes from Synpo mutant mice. Synpo-T maintains some Synpo functions, which may prevent a podocyte phenotype from emerging in unchallenged mutant mice.MethodsNovel mouse models were generated to further investigate the functions of Synpo. In one, CRISPR/Cas9 deleted most of the Synpo gene, preventing production of any detectable Synpo protein. Two other mutant strains made truncated versions of the protein. Adriamycin injections were used to challenge the mice, and Synpo functions were investigated in primary cultured podocytes.ResultsMice that could not make detectable Synpo (Synpo−/−) did not develop any kidney abnormalities up to 12 months of age. However, Synpo−/− mice were more susceptible to Adriamycin nephropathy. In cultured primary podocytes from mutant mice, the absence of Synpo caused loss of stress fibers, increased the number and size of focal adhesions, and impaired cell migration. Furthermore, loss of Synpo led to decreased RhoA activity and increased Rac1 activation.ConclusionsIn contrast to previous findings, podocytes can function normally in vivo in the absence of any Synpo isoform. Synpo plays a protective role in the context of podocyte injury through its involvement in actin reorganization and focal adhesion dynamics.
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Buřilová, Šárka, and Katarína Bielaková. "Malignant pericardial effusion as a cause of recurrent syncopes." Interní medicína pro praxi 21, no. 3 (June 30, 2019): 171–74. http://dx.doi.org/10.36290/int.2019.026.
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VANGHELUWE, Roger. "The African Synod." Louvain Studies 20, no. 1 (May 1, 1995): 65–72. http://dx.doi.org/10.2143/ls.20.1.556006.
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Yamada, Eijiro, Shuichi Okada, Tsugumichi Saito, Kihachi Ohshima, Minoru Sato, Takafumi Tsuchiya, Yutaka Uehara, Hiroyuki Shimizu, and Masatomo Mori. "Akt2 phosphorylates Synip to regulate docking and fusion of GLUT4-containing vesicles." Journal of Cell Biology 168, no. 6 (March 7, 2005): 921–28. http://dx.doi.org/10.1083/jcb.200408182.
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We have identified an unusual potential dual Akt/protein kinase B consensus phosphorylation motif in the protein Synip (RxKxRS97xS99). Surprisingly, serine 97 is not appreciably phosphorylated, whereas serine 99 is only a specific substrate for Akt2 but not Akt1 or Akt3. Although wild-type Synip (WT-Synip) undergoes an insulin-stimulated dissociation from Syntaxin4, the Synip serine 99 to phenylalanine mutant (S99F-Synip) is resistant to Akt2 phosphorylation and fails to display insulin-stimulated Syntaxin4 dissociation. Furthermore, overexpression of WT-Synip in 3T3L1 adipocytes had no effect on insulin-stimulated recruitment of glucose transporter 4 (GLUT4) to the plasma membrane, whereas overexpression of S99F-Synip functioned in a dominant-interfering manner by preventing insulin-stimulated GLUT4 recruitment and plasma membrane fusion. These data demonstrate that insulin activation of Akt2 specifically regulates the docking/fusion step of GLUT4-containing vesicles at the plasma membrane through the regulation of Synip phosphorylation and Synip–Syntaxin4 interaction.