Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Resent radar observations of asteroid 1566 Icarus

We report Doppler-only radar observations of Icarus at Goldstone at a transmitter frequency of 8510 MHz (3.5 cm wavelength) during 8-10 June 1996, the first radar detection of the object since 1968. Optimally filtered and folded spectra achieve a maximum opposite-circular (OC) polarization signal-to-noise ratio of about 10 and help to constrain Icarus' physical properties. We obtain an OC radar cross section of 0.05 km(2) (with a 35% uncertainty), which is less than values estimated by Goldstein (1969) and by Pettengill et al. (1969), and a circular polarization (SC/OC) ratio of 0.5+/-0.2. We analyze the echo power spectrum with a model incorporating the echo bandwidth B and a spectral shape parameter it, yielding a coupled constraint between B and n. We adopt 25 Hz as the lower bound on B, which gives a lower bound on the maximum pole-on breadth of about 0.6 km and upper bounds on the radar and optical albedos that are consistent with Icarus' tentative QS classification. The observed circular polarization ratio indicates a very rough near-surface at spatial scales of the order of the radar wavelength. (C) 1999 Elsevier Science Ltd. All rights reserved.

Development of a regional model for the North Indian Ocean

We have developed a one-way nested Indian Ocean regional model. The model combines the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory's (GFDL) Modular Ocean Model (MOM4p1) at global climate model resolution (nominally one degree), and a regional Indian Ocean MOM4p1 configuration with 25 km horizontal resolution and 1 m vertical resolution near the surface. Inter-annual global simulations with Coordinated Ocean-Ice Reference Experiments (CORE-II) surface forcing over years 1992-2005 provide surface boundary conditions. We show that relative to the global simulation, (i) biases in upper ocean temperature, salinity and mixed layer depth are reduced, (ii) sea surface height and upper ocean circulation are closer to observations, and (iii) improvements in model simulation can be attributed to refined resolution, more realistic topography and inclusion of seasonal river runoff. Notably, the surface salinity bias is reduced to less than 0.1 psu over the Bay of Bengal using relatively weak restoring to observations, and the model simulates the strong, shallow halocline often observed in the North Bay of Bengal. There is marked improvement in subsurface salinity and temperature, as well as mixed layer depth in the Bay of Bengal. Major seasonal signatures in observed sea surface height anomaly in the tropical Indian Ocean, including the coastal waveguide around the Indian peninsula, are simulated with great fidelity. The use of realistic topography and seasonal river runoff brings the three dimensional structure of the East India Coastal Current and West India Coastal Current much closer to observations. As a result, the incursion of low salinity Bay of Bengal water into the southeastern Arabian Sea is more realistic. (C) 2013 Elsevier Ltd. All rights reserved.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.

Impact of river runoff into the ocean on Indian summer monsoon

Rivers of the world discharge about 36000 km 3 of freshwater into the ocean every year. To investigate the impact of river discharge on climate, we have carried out two 100 year simulations using the Community Climate System Model (CCSM3), one including the river runoff into the ocean and the other excluding it. When the river discharge is shut off, global average sea surface temperature (SST) rises by about 0.5 degrees C and the Indian Summer Monsoon Rainfall (ISMR) increases by about 10% of the seasonal total with large increase in the eastern Bay of Bengal and along the west coast of India. In addition, the frequency of occurrence of La Nina-like cooling events in the equatorial Pacific increases and the correlation between ISMR and Pacific SST anomalies become stronger. The teleconnection between the SST anomalies in the Pacific and monsoon is effected via upper tropospheric meridional temperature gradient and the North African-Asian Jet axis.

Interplay of electrostatics and lipid packing determines the binding of charged polymer coated nanoparticles to model membranes

Understanding of nanoparticle-membrane interactions is useful for various applications of nanoparticles like drug delivery and imaging. Here we report on the studies of interaction between hydrophilic charged polymer coated semiconductor quantum dot nanoparticles with model lipid membranes. Atomic force microscopy and X-ray reflectivity measurements suggest that cationic nanoparticles bind and penetrate bilayers of zwitterionic lipids. Penetration and binding depend on the extent of lipid packing and result in the disruption of the lipid bilayer accompanied by enhanced lipid diffusion. On the other hand, anionic nanoparticles show minimal membrane binding although, curiously, their interaction leads to reduction in lipid diffusivity. It is suggested that the enhanced binding of cationic QDs at higher lipid packing can be understood in terms of the effective surface potential of the bilayers which is tunable through membrane lipid packing. Our results bring forth the subtle interplay of membrane lipid packing and electrostatics which determine nanoparticle binding and penetration of model membranes with further implications for real cell membranes.

Fast and slow climate responses to CO2 and solar forcing: A linear multivariate regression model characterizing transient climate change

Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

Plot Erosion Model Using Gray Relational Analysis Method

The main factors affecting interrill erosion-including runoff discharge, rainfall intensity, mean flow velocity, and slope gradient-were analyzed by using a gray relational analysis. An equation for interrill erosion was derived by coupling this analysis with dimensional and regression analyses. The values of erosion rates predicted by this equation were in good agreement with experimental observations.

A Simulation Model for Unified Interrill Erosion and Rill Erosion on Hillslopes

A mathematical model was developed for simulating runoff generation and soil erosion on hillslopes. The model is comprised of three modules: one for overland flow, one for soil infiltration, and one for soil erosion including rill erosion and interrill er

Two-Dimensional Kinematic Wave Model of Overland-Flow

A two-dimensional kinematic wave model was developed for simulating runoff generation and flow concentration on an experimental infiltrating hillslope receiving artificial rainfall. Experimental observations on runoff generation and flow concentration on irregular hillslopes showed that the topography of the slope surface controlled the direction and flow lines of overland flow. The model-simulated results satisfactorily compared with experimental observations. The erosive ability of the concentrated flow was found to mainly depend on the ratio of the width and depth of confluent grooves.

Modeling on Runoff Concentration Caused by Rainfall on Hillslopes and Application in Maoping Slope

Based on the fact that the concentration flowlines of overland flow depend on the surface landform of hillslope, a kinematic wave model was developed for simulating runoff generation and flow concentration caused by rainfall on hillslopes. The model-simulated results agree well with experimental observations. Applying the model to the practical case of Maoping slope, we obtained the characteristics of runoff generation and infiltration on the slope. Especially, the simulated results adequately reflected the confluent pattern of surface runoff, which offers a scientific foundation for designing the drainage engineering on the Maoping slope.

Modeling on Runoff and Sediment Yield in Small Watersheds

The prediction and estimate of water and soil loss is fundamental important for understanding the effect of the spatial heterogeneity of underlying surfaces and preventing ecological environment deterioration. In this paper, a dynamic model of runoff and sediment yield in small watersheds is established. The proposed model includes three components: runoff generation caused by rainfall, soil erosion on hillslopes by overland flow, and runoff concentration and sediment transport on watersheds. Applying the proposed model, the runoff and sediment yield processes in a typical catchment on the loess plateau was estimated, which exhibited a good agreement between predicted results and observation.

Do oil and gas platforms off California reduce recruitment of bocaccio (Sebastes paucispinis) to natural habitat? An analysis based on trajectories derived from high-frequency radar

To investigate the possibility that oil and gas platforms may reduce recruitment of rockfishes (Sebastes spp.) to natural habitat, we simulated drift pathways termed “trajectories” in our model) from an existing oil platform to nearshore habitat using current measurements from high-frequency (HF) radars. The trajectories originated at Platform Irene, located west of Point Conception, California, during two recruiting seasons for bocaccio (Sebastes paucispinis): May through August, 1999 and 2002. Given that pelagic juvenile bocaccio dwell near the surface, the trajectories estimate transport to habitat. We assumed that appropriate shallow water juvenile habitat exists inshore of the 50-m isobath. Results from 1999 indicated that 10% of the trajectories represent transport to habitat, whereas 76% represent transport across the offshore boundary. For 2002, 24% represent transport to habitat, and 69% represent transport across the offshore boundary. Remaining trajectories (14% and 7% for 1999 and 2002, respectively) exited the coverage area either northward or southward along isobaths. Deployments of actual drifters (with 1-m drogues) from a previous multiyear study provided measurements originating near Platform Irene from May through August. All but a few of the drifters moved offshore, as was also shown with the HF radar-derived trajectories. These results indicate that most juvenile bocaccio settling on the platform would otherwise have been transported offshore and perished in the absence of a platform. However, these results do not account for the swimming behavior of juvenile bocaccio, about which little is known.

A multi-basin seasonal streamflow model for the Sierra Nevada

Linear regression models are constructed to predict seasonal runoff by fitting streamflow to temperature, precipitation, and snow water content across a range of elevations. The models are quite successful in capturing the differences in discharge between different elevation watersheds and their interannual variations. This exercise thus provides insight into seasonal changes in streamflow at different elevation watersheds that might occur under a changed climate.

Semiempirical down-scaling of GCM output to the local scale for temperature, precipitation, and runoff

EXTRACT (SEE PDF FOR FULL ABSTRACT): An empirically derived multiple linear regression model is used to relate a local-scale dependent variable (either temperature, precipitation, or surface runoff) measured at individual gauging stations to six large-scale independent variables (temperature, precipitation, surface runoff, height to the 500-mbar pressure surface, and the zonal and meridional gradient across this surface). ...The area investigated is the western United States. ... The calibration data set is from 1948 through 1988 and includes data from 268 joint temperature and precipitation stations, 152 streamflow stations (which are converted to runoff data), and 24 gridded 500-mbar pressure height nodes.