Radijus utjecaja oborine nad područjem monsuna u Indiji

The paper describes an analysis of rain gauge data to determine an appropriate radius of influence to use for the objective analysis of rainfall over Indian monsoon region. The correlation co-efficient (CC) of rainfall between rain gauges in discrete distance intervals is computed, and the distance at which CC falls to 0.3 is chosen as the radius of rainfall influence. The method is applied for the monthly mean rainfall observations for June, July and August of Indian summer monsoon 2001. The method is also tested for a few case studies in relation to varying geographical and synoptic situations. The study shows that the radius of influence of rainfall over Indian region, in general, is around 200 km, but it has certain day to day variations depending on the prevailing synoptic conditions. The finding of the study is expected to be very useful for the objective analysis of rainfall over Indian region.Ova studija prikazuje analizu mjerenja kišomjernih postaja radi određivanja odgovarajućeg radijusa utjecaja za potrebe objektivne analize oborine nad područjem monsuna u Indiji. Računao se koeficijent korelacije oborine između kišomjernih postaja na diskretnim intervalima te je koeficijent korelacije od 0.3 odabran kao radijus oborinskog utjecaja. Metoda je primijenjena na srednje mjesečne vrijednosti oborine za razdoblje lipanj-kolovoz 2001. tijekom ljetnog monsuna u Indiji. Ova je metoda također testirana na nekoliko odabranih slučajeva zbog variranja geografskih i sinoptičkih situacija. Studija pokazuje da je radijus utjecaja oborine nad područjem monsuna u Indiji općenito oko 200 km, iako postoji određena dnevna varijabilnost koja ovisi o prevladavajućim sinoptičkim uvjetima. Rezultati ove studije korisni su za potrebe objektivne analize oborine nad područjem Indij

Unutarsezonska varijabilnost naoblake nad indijskim potkontinentom tijekom monsunske sezone na temelju mjerenja oborine radarom TRMM

The intra-seasonal variability of the Indian summer monsoon, which manifests in the form of “active” and “break” phases in rainfall, is investigated with respect to the variability of the convective and stratiform precipitating cloud pattern over the region. Long period data from TRMM PR satellite (2A23 and 3B42 datasets) for the monsoon season of 2002 to 2010 over the Indian subcontinent is used for this purpose. The study reveals that the most significant spatial variation in convective and stratiform cloud amount in relation to the active and break phase occurs over the monsoon trough region in central India. The active phase is characterized by positive convective (~5%) and stratiform (~20%) precipitating cloud anomalies over this region. However, the maximum of the former precedes the latter by 1–2 days leading up to the active phase, indicating that the stratiform build up, is due to the gradual organization of the convective cloud systems over the region. The days leading up to the break phase are marked by negative anomalies in the convective and stratiform fractions of cloudiness over this region, which are in phase with each other, unlike the lead-up to the active phase. Analysis of the pattern of atmospheric heat source and sinks over the region from the NCEP–NCAR re-analysis data indicates that the engine for the growth/decay of convection over the monsoon trough region lies primarily in the Bay of Bengal and adjacent east India. The active phase is preceded by a heating pattern that promotes large scale, organized convective cloud growth over the Bay of Bengal preceding the actual onset, while the heating pattern leading up to the break phase promotes the formation of isolated convective clouds and decay of cloud organization over the monsoon trough region.U radu je ispitana unutarsezonska varijabilnost indijskog ljetnog monsuna, koja se očituje izmjenom „aktivnih“ faza i faza „stanke“ u polju oborine, obzirom na varijabilnost konvektivne i stratiformne naoblake nad razmatranim područjem. U tu su svrhu analizirane monsunske sezone nad indijskim potkontinentom za razdoblje od 2002. do 2010. godine na temelju dugačkog niza podataka dobivenih pomoću satelita TRMM PR (podaci 2A23 i 3B42). Pokazano je da se najznačajnije prostorne promjene konvektivne i stratiformne naoblake povezane s aktivnom fazom i fazom stanke javljaju u području monsunske doline u polju tlaka zraka nad središnjom Indijom. Aktivnu fazu karakteriziraju pozitivne anomalije konvektivne (~5%) i stratiformne (~20%) naoblake. Međutim, maksimum konvektivne naoblake prethodi maksimumu stratiformne naoblake i javlja se 1–2 dana prije nastupa same aktivne faze, što ukazuje na to da do porasta stratiformne naoblake dolazi zbog postepenog organiziranja sustava konvektivne naoblake nad razmatranim područjem. Fazi stanke prethode dani s negativnim anomalijama konvektivne i stratiformne naoblake nad razmatranim područjem, a njihov je razvoj istovremen za razliku od aktivne faze, kojoj prethode pozitivne anomalije konvektivne naoblake. Analiza polja atmosferskih izvora i ponora topline na temelju podataka NCEP-NCAR reanalize ukazala je na Bengalski zaljev i istočnu Indiju kao područja s glavnim uzročnicima porasta/smanjenja konvekcije u području monsunske doline u polju tlaka zraka. Aktivnoj fazi prethodi raspodjela izvora i ponora topline, koja podržava razvoj sustava velike skale, te sustavni porast konvektivne naoblake nad Bengalskim zaljevom, koji prethodi njenom samom početku, dok fazi stanke prethodi takva raspodjela izvora i ponora topline koja podržava razvoj izoliranih konvektivnih oblaka i potiskuje organizirano formiranje sustava oblaka nad područjem monsunske doline u polju tlaka zraka

Vefrifikacija prognoza oborine WRF modelom nad Indijom tijekom monsuna 2010.: CRA metoda

The WRF model forecast during monsoon season 2010 has been verified with daily observed gridded rainfall analysis with 0.5° spatial resolution. First- ly, the conventional neighborhood technique has been deployed to calculate common scores like mean error and root mean square error. Along with, widely used two categorical skill scores have been computed for seven different rainfall thresholds. The scores only found the general nature of the model performance and depicted the degradation of forecast accuracy exceeding moderate rainfall category of 7.5 mm. The object oriented Contiguous Rain Area method also has been considered for the verification of rainfall forecasts to gather more informa- tion about model performance. The method similarly has endorsed that the performance of the model degrades along with the increase in rainfall amount. But at the same time, the decomposition of mean square error has pointed out that the maximum error occurred due the shifting of rain object or event in the forecast compared to observation. The volume error contributes less as compared to pattern error in 24 hour forecasts irrespective of rainfall thresholds. But in 48 hour forecasts, their values are comparable and change along with rainfall threshold. During whole monsoon season, all contiguous rain areas in model forecasts have been searched over observed rainfall analyses applying best-fit criteria. For contiguous rain areas below 50 mm more than 70 percent match was found.Prognoza oborine dobivena modelom WRF za monsunsku sezonu 2010. verificirana je korištenjem analize dnevne opažene oborine u mreži prostorne rezolucije od 0,5°. Određeni su jednostavni, standardni pokazatelji poput srednje pogreške i srednje kvadratne pogreške, a također i dva uobičajena kategorička pokazatelja uspješnosti koji su izračunati za sedam različitih pragova oborine. Ti pokazatelji su omogućili općenitu procjenu uspješnosti modela te su ukazali na smanjenu pouzdanost za kategorije oborine veće od 7,5 mm. kako bi se detaljnije procijenila uspješnost modela, verifikacija prognoze oborine je također napravljena pomoću objektno orijentirane metode bliskih oborinskih područja CRA (Contiguous Rain Area). Ova metoda je također ukazala na smanjenje uspješnosti modela s povećanjem količine oborine. Međutim, dekompozicija srednje kvadratne pogreške je ukazala da najveću pogrešku uzrokuje pomak prognoziranog oborinskog područja ili događaja u odnosu na izmjerene vrijednosti. Za 24-satne prognoze volumna pogreška doprinosi manje u usporedbi s prostornom pogreškom, neovisno o pragovima oborine. Međutim, za 48-satne prognoze iznosi volumne i prostorne pogreške su usporedivi te rastu s pragom oborine. Susjedna oborinska područja za prognoziranu oborinu su određena obzirom na izmjerenu oborinu primjenom kriterija nabolje podudarnosti. Postupak je proveden za cijelu monsunsku sezonu. Za područja s količinom oborine manjom od 50 mm podudaranje je veće od 70%

Višemodelna ansambl metoda (MME) za prognozu putanja ciklona preko Sjevernoindijskog mora

A multimodel ensemble (MME) technique for predicting track of tropical cyclones over the North Indian Sea has been proposed. The technique is developed applying multiple linear regression procedure. Parameters of the ensemble technique are determined from the forecast datasets on the tracks of tropical cyclones over the North Indian Sea during the year 2008-2009. The parameters selected as predictors are: forecast latitude and longitude positions at 12-hour interval up to 72-hours forecast of five operational numerical weather prediction models. The dynamical models included for development of the ensemble technique are: (i) forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF), (ii) the National Centers for Environmental Prediction Global Forecast System (NCEP), (iii) the MM5 model, (iv) the Quasi-Lagrangian model (QLM) and (v) the model of Japan Meteorological Agency (JMA). A collective bias correction is included in the ensemble technique in which a multiple linear regression based minimization principle for the model forecast position against to the observed position is applied. These bias factors are described by separate weights at every 12-hours interval up to the 72-hour forecasts for each of the member model. When the technique is tested with the independent samples, forecast skill of the MME technique is found to be reasonably good. The average error ranges from of the order of 74 km to 290 km for forecasts up to 72-hour. Performance of the MME technique shows that there are skill improvements up to 30 km for the position errors over the best model at 72-hour forecast. The forecast skill of the MME technique for forecasts up to 72-hour also shows an improvement as compared to the forecasts from member models and the simple ensemble mean (ENM).U ovom radu predlaže se metoda za višemodelnu ansambl prognozu (MME) putanja tropskih ciklona nad sjevernim dijelom Indijskog oceana korištenjem prognoza nekoliko različitih modela. Metoda je razvijena na temelju višestruke linearne regresije. Parametri MME metode određuju se pomoću prognoziranih podataka putanja tropskih ciklona nad sjevernim dijelom Indijskog oceana u razdoblju 2008.–2009. Odabrani parametri su: prognozirana zemljopisna širina i dužina položaja ciklona u 12-satnom intervalu u 72-satnoj prognozi za pet operativnih numeričkih prognostičkih modela. Korišteni članovi ansambla u MME metodi su: (i) prognoze Europskog centra za srednjoročne prognoze vremena (ECMWF), (ii) prognoze Nacionalnog centra za zaštitu okoliša prognostičkog globalnog sustava (NCEP), (iii) MM5 model, (iv) kvazi-Lagrangian model (QLM) i (v) model Japanske meteorološke agencije (JMA). Koristeći višestruku linearnu regresiju između opaženih i modelima prognoziranih putanja, predložena metoda uključuje i smanjenje sveukupne srednje pogreške. Odgovarajući čimbenici odstupanja opisuju se odvojenim te šinama u svakom 12-satnom intervalu u cijeloj 72-satnoj prognozi za svaki pojedini model. Nakon testiranja metode na nezavisnim uzorcima pokazalo se da je uspješnost prognoze MME metodom zadovoljavajuća. Srednja pogreška je za 72-h prognoze unutar intervala od 74 km do 290 km. Performanse MME metode pokazuju da je poboljšanje uspješnosti do 30 km prilikom određivanja pogreške pozicije ciklone za najbolji model unutar 72-satne prognoze. Uspješnost prognoze pomoću MME metode za prognoze do 72-sata tako|er pokazuju poboljšanje u usporedbi s prognozama kako svakog pojedinačnog modela, tako i s prognozom temeljenom na jednostavnom srednjaku ansambla

Poboljšanje kvalitete INSAT izvedenih procjena količinske oborine korištenjem metode neuronske mreže

In this paper an Artificial Neural Network (NN) approach has been applied to improve the quality of the INSAT derived sub-division quantitative precipitation estimates (IMD-QPE) over the Indian region for the summer monsoon season. Data for the years 2001, 2003 and 2004 have been used as the training sample. The method is tested with independent sample data for the year 2005. For the subdivisions over the domains of high orographic and monsoon low pressure system, where very rainfall occasionally occurs, different network architectures are applied to minimize the IMD-QPE errors. An inter-comparison between NNQPE (NN model output IMD-QPE), IMD-QPE and actual rainfall indicates that the pattern of NNQPE is closer to the observed rainfall distribution. The weekly mean absolute error of IMD-QPE with respect to observed rainfall, which ranges between 10–99 mm, becomes 4–70 mm in case of NNQPE. The performance statistics shows that the proposed NN model is able to produce better IMD-QPE with higher skill score and correlation co-efficient with respect to observation in most of the sub-divisions. The method is found to be promising for operational application.U ovoj studiji se koristi umjetna neuronska mreža (NN) za poboljšanje INSAT izvedenih podrazreda procjena količinske oborine (IMD-QPE) nad područjem Indije tijekom sezone ljetnog monsuna. Korišteni su podaci za 2001., 2003. i 2004. godinu kao probni uzorak. Metoda se testira na nezavisnom skupu podataka iz 2005. Za podrazrede nad domenama visokog orografskog tlaka i monsunskog niskog tlaka gdje se opažaju vrlo jake kiše, primijenila se različita mrežna arhitektura radi minimaliziranja IMD-QPE grešaka. Usporedba između NNQPE (izlaz IMD-QPE NN modela), IMD-QPE i stvarne oborine upućuje da je uzorak NNQPE bliži opaženoj distribuciji oborine. Tjedna srednja apsolutna pogreška IMD-QPE u odnosu na opaženu oborinu, koja se nalazi unutar intervala od 10–99 mm, postaje 4–70 mm u slučaju NNQPE. Statistika je pokazala da je predloženi NN model sposoban bolje reproducirati IMD-QPE s boljim pokazateljima uspješnosti i koeficijentima korelacije u odnosu na opažanja u većini podrazreda. Pokazano je da se metoda može uspješno primijeniti u svakodnevnoj praksi

Small Quadrupole Deformation for the Dipole Bands in 112In

High spin states in $^{112}$In were investigated using $^{100}$Mo($^{16}$O, p3n) reaction at 80 MeV. The excited level have been observed up to 5.6 MeV excitation energy and spin $\sim$ 20$\hbar$ with the level scheme showing three dipole bands. The polarization and lifetime measurements were carried out for the dipole bands. Tilted axis cranking model calculations were performed for different quasi-particle configurations of this doubly odd nucleus. Comparison of the calculations of the model with the B(M1) transition strengths of the positive and negative parity bands firmly established their configurations.Comment: 10 pages, 11 figures, 2 table

Four quasi-particle level at 2256 keV in <SUP>182</SUP>Re

In-beam nuclear spectroscopic studies of 182Re, following the reaction 181Ta(&#945;,3n)182Re have been made using gamma-ray and internal conversion electron techniques. K-conversion coefficients for several transitions have been measured and the multi-polarities of the various transitions assigned. In particular, the spin and parity of the four-quasi-particle isomeric level at 2256 keV were determined to be 16-. The g-factor of this level has been measured to be g=0.32&#177;0.05. On the basis of theg-factor and the decay pattern of this level, a configuration {v9/2+[624&#8593;]v7/2-[514&#8595;]v7/2- [503&#8593;]&#960;9/2-[514&#8593;]}&#954;&#960;=16- has been assigned to this level. The nature of the retardation of the gamma transitions deexciting this level is discussed. It is argued that the measured retardation factors can be explained if the nucleus has a triaxial shape