A Stochastic Fractional Dynamics Model of Space-time Variability of Rain

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment

The Escape of Gravitational Radiation from the Field of Massive Bodies

We consider a compact source of gravitational waves of frequency $\omega$, in or near a massive spherically symmetric distribution of matter or a black hole. Recent calculations have led to apparently contradictory results for the influence of the massive body on the propagation of the waves. We show here that the results are in fact consistent and in agreement with the ``standard'' viewpoint in which the high frequency compact source produces the radiation as if in a flat background, and the background curvature affects the propagation of these waves.Comment: RevTeX, 11pp, UU-HEP-92/1

Using Plasmodium knowlesi as a model for screening Plasmodium vivax blood-stage malaria vaccine targets reveals new candidates.

Plasmodium vivax is responsible for the majority of malaria cases outside Africa. Unlike P. falciparum, the P. vivax life-cycle includes a dormant liver stage, the hypnozoite, which can cause infection in the absence of mosquito transmission. An effective vaccine against P. vivax blood stages would limit symptoms and pathology from such recurrent infections, and therefore could play a critical role in the control of this species. Vaccine development in P. vivax, however, lags considerably behind P. falciparum, which has many identified targets with several having transitioned to Phase II testing. By contrast only one P. vivax blood-stage vaccine candidate based on the Duffy Binding Protein (PvDBP), has reached Phase Ia, in large part because the lack of a continuous in vitro culture system for P. vivax limits systematic screening of new candidates. We used the close phylogenetic relationship between P. vivax and P. knowlesi, for which an in vitro culture system in human erythrocytes exists, to test the scalability of systematic reverse vaccinology to identify and prioritise P. vivax blood-stage targets. A panel of P. vivax proteins predicted to function in erythrocyte invasion were expressed as full-length recombinant ectodomains in a mammalian expression system. Eight of these antigens were used to generate polyclonal antibodies, which were screened for their ability to recognize orthologous proteins in P. knowlesi. These antibodies were then tested for inhibition of growth and invasion of both wild type P. knowlesi and chimeric P. knowlesi lines modified using CRISPR/Cas9 to exchange P. knowlesi genes with their P. vivax orthologues. Candidates that induced antibodies that inhibited invasion to a similar level as PvDBP were identified, confirming the utility of P. knowlesi as a model for P. vivax vaccine development and prioritizing antigens for further follow up.European Union, National Institutes of Health (US

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign