Satellite rainfall retrieval by logistic regression

The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed

Trends and Variations of Ocean Surface Latent Heat Flux: Results from GSSTF2c Data Set

Trends and variations of Goddard Satellite-based Surface Turbulent Fluxes (GSSTF) version 2c (GSSTF2c) latent heat flux (LHF) are examined. This version of LHF takes account of the correction in Earth incidence angle. The trend of global mean LHF for GSSTF2c is much reduced relative to GSSTF version 2b Set 1 and Set 2 for the same period 1988-2008. Temporal increase of GSSTF2c LHF in the two decades is 11.0%, in which 3.1%, 5.8%, and 2.1% are attributed to the increase in wind, the increase in sea surface saturated air humidity, and the decrease in near-surface air humidity, respectively. The first empirical orthogonal function of LHF is a conventional El Nino Southern Oscillation (ENSO) mode. However, the trends in LHF are independent of conventional ENSO phenomena. After removing ENSO signal, the pattern of LHF trends is primarily determined by the pattern of air-sea humidity difference trends

Technical Report Series on Global Modeling and Data Assimilation

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates

Thin liquid water clouds: their importance and our challenge

Many clouds important to the Earth’s energy balance contain small amounts of liquid water, yet despite many improvements, large differences in retrievals of their liquid water amount and particle size still must be resolved

Magnetic moment of the pentaquark Θ+(1540)\Theta^+(1540) with light-cone QCD sum rules

In this article, we study the magnetic moment of the pentaquark state $\Theta^+(1540)$ as diquark-diquark-antiquark ($[ud][ud]\bar{s}$) state in the framework of the light-cone QCD sum rules approach. The numerical results indicate the magnetic moment of the pentaquark state $\Theta^+(1540)$ is about $\mu_{\Theta^+}=-(0.49\pm 0.06)\mu_N$.Comment: 10 pages, 1 figure. The main contents of this article is included in hep-ph/0503007, this article will not be submitted to a journal for publicatio

Frequency Shift of Carbon-Nanotube-Based Mass Sensor Using Nonlocal Elasticity Theory

The frequency equation of carbon-nanotube-based cantilever sensor with an attached mass is derived analytically using nonlocal elasticity theory. According to the equation, the relationship between the frequency shift of the sensor and the attached mass can be obtained. When the nonlocal effect is not taken into account, the variation of frequency shift with the attached mass on the sensor is compared with the previous study. According to this study, the result shows that the frequency shift of the sensor increases with increasing the attached mass. When the attached mass is small compared with that of the sensor, the nonlocal effect is obvious and increasing nonlocal parameter decreases the frequency shift of the sensor. In addition, when the location of the attached mass is closer to the free end, the frequency shift is more significant and that makes the sensor reveal more sensitive. When the attached mass is small, a high sensitivity is obtained

Estimation of colorectal adenoma recurrence with dependent censoring

<p>Abstract</p> <p>Background</p> <p>Due to early colonoscopy for some participants, interval-censored observations can be introduced into the data of a colorectal polyp prevention trial. The censoring could be dependent of risk of recurrence if the reasons of having early colonoscopy are associated with recurrence. This can complicate estimation of the recurrence rate.</p> <p>Methods</p> <p>We propose to use midpoint imputation to convert interval-censored data problems to right censored data problems. To adjust for potential dependent censoring, we use information from auxiliary variables to define risk groups to perform the weighted Kaplan-Meier estimation to the midpoint imputed data. The risk groups are defined using two risk scores derived from two working proportional hazards models with the auxiliary variables as the covariates. One is for the recurrence time and the other is for the censoring time. The method described here is explored by simulation and illustrated with an example from a colorectal polyp prevention trial.</p> <p>Results</p> <p>We first show that midpoint imputation under an assumption of independent censoring will produce an unbiased estimate of recurrence rate at the end of the trial, which is often the main interest of a colorectal polyp prevention trial, and then show in simulations that the weighted Kaplan-Meier method using the information from auxiliary variables based on the midpoint imputed data can improve efficiency in a situation with independent censoring and reduce bias in a situation with dependent censoring compared to the conventional methods, while estimating the recurrence rate at the end of the trial.</p> <p>Conclusion</p> <p>The research in this paper uses midpoint imputation to handle interval-censored observations and then uses the information from auxiliary variables to adjust for dependent censoring by incorporating them into the weighted Kaplan-Meier estimation. This approach can handle a situation with multiple auxiliary variables by deriving two risk scores from two working PH models. Although the idea of this approach might appear simple, the results do show that the weighted Kaplan-Meier approach can gain efficiency and reduce bias due to dependent censoring.</p

Motivation and Knowledge Sharing through Social Media within Danish Organizations

Part 3: Creating Value through ApplicationsInternational audienceBased on an empirical quantitative study, this article investigates employee motivation in Danish companies and aims at determining which factors affect employees’ knowledge sharing through social media in a working environment. Our findings pinpoint towards the potential social media have for enhancing internal communication, knowledge sharing and collaboration in organizations, but the adoption is low, at this point, due to mainly organizational and individual factors. Technological factors do not seem to affect employees’ motivation for knowledge sharing as much as previous research has found, but it is the influence from the combination of individual and organizational factors, which affect the adoption of the platforms. A key finding in the study is that knowledge sharing is not a ‘social dilemma’ as previous studies have found. The study shows a positive development in employees’ willingness to share knowledge, because knowledge sharing is considered more beneficial than to hoard it