Reduced non-Gaussianity by 30s rapid update in convective-scale numerical weather prediction

Non-Gaussian forecast error is a challenge for ensemble-based data assimilation (DA), particularly for more nonlinear convective dynamics. In this study, we investigate the degree of the non-Gaussianity of forecast error distributions at 1km resolution using a 1000-member ensemble Kalman filter, and how it is affected by the DA update frequency and observation number. Regional numerical weather prediction experiments are performed with the SCALE (Scalable Computing for Advanced Library and Environment) model and the LETKF (local ensemble transform Kalman filter) assimilating phased array radar observations every 30s. The results show that non-Gaussianity develops rapidly within convective clouds and is sensitive to the DA frequency and the number of assimilated observations. The non-Gaussianity is reduced by up to 40% when the assimilation window is shortened from 5min to 30s, particularly for vertical velocity and radar reflectivity.Fil: Ruiz, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; Argentina. Rikagaku Kenkyujo; JapónFil: Lien, Guo-Yuan. Central Weather Bureau, Taiwan; ArgentinaFil: Kondo, Keiichi. Meteorological Research Institute; JapónFil: Otsuka, Shigenori. Rikagaku Kenkyujo; JapónFil: Miyoshi, Takemasa. Rikagaku Kenkyujo; Japón. University of Maryland; Estados Unidos. Japan Agency for Marine-Earth Science and Technology; Japó

Coincidence analysis to search for inspiraling compact binaries using TAMA300 and LISM data

Japanese laser interferometric gravitational wave detectors, TAMA300 and LISM, performed a coincident observation during 2001. We perform a coincidence analysis to search for inspiraling compact binaries. The length of data used for the coincidence analysis is 275 hours when both TAMA300 and LISM detectors are operated simultaneously. TAMA300 and LISM data are analyzed by matched filtering, and candidates for gravitational wave events are obtained. If there is a true gravitational wave signal, it should appear in both data of detectors with consistent waveforms characterized by masses of stars, amplitude of the signal, the coalescence time and so on. We introduce a set of coincidence conditions of the parameters, and search for coincident events. This procedure reduces the number of fake events considerably, by a factor $\sim 10^{-4}$ compared with the number of fake events in single detector analysis. We find that the number of events after imposing the coincidence conditions is consistent with the number of accidental coincidences produced purely by noise. We thus find no evidence of gravitational wave signals. We obtain an upper limit of 0.046 /hours (CL $= 90$) to the Galactic event rate within 1kpc from the Earth. The method used in this paper can be applied straightforwardly to the case of coincidence observations with more than two detectors with arbitrary arm directions.Comment: 28 pages, 17 figures, Replaced with the version to be published in Physical Review

Results of the search for inspiraling compact star binaries from TAMA300's observation in 2000-2004

We analyze the data of TAMA300 detector to search for gravitational waves from inspiraling compact star binaries with masses of the component stars in the range 1-3Msolar. In this analysis, 2705 hours of data, taken during the years 2000-2004, are used for the event search. We combine the results of different observation runs, and obtained a single upper limit on the rate of the coalescence of compact binaries in our Galaxy of 20 per year at a 90% confidence level. In this upper limit, the effect of various systematic errors such like the uncertainty of the background estimation and the calibration of the detector's sensitivity are included.Comment: 8 pages, 4 Postscript figures, uses revtex4.sty The author list was correcte

Observation results by the TAMA300 detector on gravitational wave bursts from stellar-core collapses

We present data-analysis schemes and results of observations with the TAMA300 gravitational-wave detector, targeting burst signals from stellar-core collapse events. In analyses for burst gravitational waves, the detection and fake-reduction schemes are different from well-investigated ones for a chirp-wave analysis, because precise waveform templates are not available. We used an excess-power filter for the extraction of gravitational-wave candidates, and developed two methods for the reduction of fake events caused by non-stationary noises of the detector. These analysis schemes were applied to real data from the TAMA300 interferometric gravitational wave detector. As a result, fake events were reduced by a factor of about 1000 in the best cases. The resultant event candidates were interpreted from an astronomical viewpoint. We set an upper limit of 2.2x10^3 events/sec on the burst gravitational-wave event rate in our Galaxy with a confidence level of 90%. This work sets a milestone and prospects on the search for burst gravitational waves, by establishing an analysis scheme for the observation data from an interferometric gravitational wave detector

Stable Operation of a 300-m Laser Interferometer with Sufficient Sensitivity to Detect Gravitational-Wave Events within our Galaxy

TAMA300, an interferometric gravitational-wave detector with 300-m baseline length, has been developed and operated with sufficient sensitivity to detect gravitational-wave events within our galaxy and sufficient stability for observations; the interferometer was operated for over 10 hours stably and continuously. With a strain-equivalent noise level of $h\sim 5 \times 10^{-21} /\sqrt{\rm Hz}$, a signal-to-noise ratio (SNR) of 30 is expected for gravitational waves generated by a coalescence of 1.4 $M_\odot$-1.4 $M_\odot$ binary neutron stars at 10 kpc distance. %In addition, almost all noise sources which limit the sensitivity and which %disturb the stable operation have been identified. We evaluated the stability of the detector sensitivity with a 2-week data-taking run, collecting 160 hours of data to be analyzed in the search for gravitational waves.Comment: 5 pages, 4 figure

A Time-Lagged Ensemble Simulation on the Modulation of Precipitation over West Java in January–February 2007

A numerical experiment using a regional nonhydrostatic model is performed to investigate the synoptic condition related to the heavy precipitation event that occurred at Jakarta in West Java, Indonesia, in January–February 2007. A time-lagged ensemble forecast method is employed with nine ensemble members. The ensemble mean well reproduces the temporal modulation of the spatial distributions of precipitation obtained from the Tropical Rainfall Measuring Mission data. During the simulated two months, several monsoon surges are observed, but only the surge event during which the Jakarta flood event occurred is associated with a cold anomaly. The top of the cold northerly is about 1.5 km. The cold surge event is preceded by the so-called Borneo vortex event, which is dominated by a cyclonic vortex around Borneo, Indonesia, with a horizontal scale of 1000 km and a vertical scale of 3 km. An analysis of cumulative distribution functions in a pentad time scale shows the modulation of the probability of rainfall rate. In pentad 7 (31 January–4 February), which includes the heavy rainfall event, the fraction of the area with precipitation is the highest and the contribution of heavy rainfall to the total amount is one of the highest in the two-month period. The diurnal cycle of occurrence of heavy rainfall is also modulated; in pentad 7, semidiurnal variation becomes dominant, and the largest peak appears in the early morning

An Experimental Numerical Weather Prediction in Indochina Region with a Meso-Scale Model

We perform a downscaling hindcast experiment in Indochina region with a fine-mesh meso-scale regional model under the assumption of the "perfect forecast" produced by a global numerical weather prediction model. The experiment is done for July and August in the wet Southwest Monsoon period. Validations of the downscaling hindcasts are done with surface station data of temperature and accumulated rainfall in Lao PDR. Some improvements in the downscaling hindcast are attained as a result of the better resolution of the surface topography. Further application of this kind of downscaling forecasts is discussed.We perform a downscaling hindcast experiment in Indochina region with a fine-mesh meso-scale regional model under the assumption of the "perfect forecast" produced by a global numerical weather prediction model. The experiment is done for July and August in the wet Southwest Monsoon period. Validations of the downscaling hindcasts are done with surface station data of temperature and accumulated rainfall in Lao PDR. Some improvements in the downscaling hindcast are attained as a result of the better resolution of the surface topography. Further application of this kind of downscaling forecasts is discussed

メソモデルによるインドシナ域でのダウンスケール数値天気予報実験

全球数値天気予報モデルによって「完璧な天気予報」が為されたという仮定の下で，高解像メソスケール領域モデルを用いてインドシナ地域においてダウンスケールハインドキャスト実験を行った。実験は雨季である6月縲・月について2003年縲・006年の4年間に対して行い，実験結果の検証にはラオスの地表観測点17点の気温を用いた。ここでは散布図を用いて観測との相関係数やバイアスの改善を評価する方法を提案する。観測とモデル結果の相関係数は7月と9月に高く6月と8月に低かった。バイアスは各地点の地形表現の誤差に伴うバイアスに加えて領域モデル結果においては全地点において約1 Kのバイアスが見られた。We perform a downscaling hindcast experiment in Indochina region with a fine-mesh mesoscale regional model under the assumption of the "perfect forecast" produced by a global numerical weather prediction model. The experiment is done for June-to-September of the years 2003-to-2006 in the rainy season. Validations of the downscaling hindcast are made with temperature data obtained at 17 surface stations in Laos. We propose a new method to diagnose the improvement of correlation or bias by the downscaling using a scatter diagram. The correlation between the model results and observations is higher in July and September than that in June or August. We find a rather common bias for all the stations of about 1 K in the model in addition to the bias due to the elevation error of each station.全球数値天気予報モデルによって「完璧な天気予報」が為されたという仮定の下で，高解像メソスケール領域モデルを用いてインドシナ地域においてダウンスケールハインドキャスト実験を行った。実験は雨季である6月縲・月について2003年縲・006年の4年間に対して行い，実験結果の検証にはラオスの地表観測点17点の気温を用いた。ここでは散布図を用いて観測との相関係数やバイアスの改善を評価する方法を提案する。観測とモデル結果の相関係数は7月と9月に高く6月と8月に低かった。バイアスは各地点の地形表現の誤差に伴うバイアスに加えて領域モデル結果においては全地点において約1 Kのバイアスが見られた。We perform a downscaling hindcast experiment in Indochina region with a fine-mesh mesoscale regional model under the assumption of the "perfect forecast" produced by a global numerical weather prediction model. The experiment is done for June-to-September of the years 2003-to-2006 in the rainy season. Validations of the downscaling hindcast are made with temperature data obtained at 17 surface stations in Laos. We propose a new method to diagnose the improvement of correlation or bias by the downscaling using a scatter diagram. The correlation between the model results and observations is higher in July and September than that in June or August. We find a rather common bias for all the stations of about 1 K in the model in addition to the bias due to the elevation error of each station