Cloud computing and virtualization within the regional climate model and evaluation system

The Regional Climate Model Evaluation System (RCMES) facilitates the rapid, flexible inclusion of NASA observations into climate model evaluations. RCMES provides two fundamental components. A database (RCMED) is a scalable point-oriented cloud database used to elastically store remote sensing observations and to make them available using a space time query interface. The analysis toolkit (RCMET) is a Python-based toolkit that can be delivered as a cloud virtual machine, or as an installer package deployed using Python Buildout to users in order to allow for temporal and spatial regridding, metrics calculation (RMSE, bias, PDFs, etc.) and end-user visualization. RCMET is available to users in an “offline”, lone scientist mode based on a virtual machine dynamically constructed with model outputs and observations to evaluate; or on an institution’s computational cluster seated close to the observations and model outputs. We have leveraged RCMES within the content of the Coordinated Regional Downscaling Experiment (CORDEX) project, working with the University of Cape Town and other institutions to compare the model output to NASA remote sensing data; in addition we are also working with the North American Regional Climate Change Assessment Program (NARCCAP). In this paper we explain the contribution of cloud computing to RCMES’s specifically describing studies of various cloud databases we evaluated for RCMED, and virtualization toolkits for RCMET, and their potential strengths in delivering user-created dynamic regional climate model evaluation virtual machines for our users.     

Towards bridging the gap between climate change projections and maize producers in South Africa

Theoretical and Applied Climatology - Multi-decadal regional projections of future climate change are introduced into a linear statistical model in order to produce an ensemble of austral...     

The coupling of cloud base height and surface fluxes: a transferability intercomparison

This paper presents an evaluation of the simulated coupling between cloud base height (CBH) and surface fluxes over selected Coordinated Enhanced Observing Period (CEOP) reference stations by five regional climate models as part of a transferability intercomparison experiment. The model results are compared with station data obtained during the first phase of the CEOP measuring campaigns. The models gave a credible simulation of both diurnal and seasonal cycles of cloud base height and surface variables over the stations. However, the models exhibited some difficulty in reproducing the diurnal and seasonal temperatures over the tropical stations. The study used principal component analysis to show that three factors account for most of the variability in the observed and simulated data and to investigate the coupling between cloud base height and surface fluxes in the data. In the observations, CBH is well coupled with the surface fluxes over Cabauw, Bondville, Lamont, and Berms, but coupled only with temperature over Lindenberg and Tongyu. All models but GEMLAM simulate substantial coupling between CBH and surface fluxes at all stations; GEMLAM does not couple CBH with surface fluxes, but with surface temperature and specific humidity.     

Interrogating empirical-statistical downscaling

The delivery of downscaled climate information is increasingly seen as a vehicle of climate services, a driver for impacts studies and adaptation decisions, and for informing policy development. Empirical-statistical downscaling (ESD) is widely used; however, the accompanying responsibility is significant, and predicated on effective understanding of the limitations and capabilities of ESD methods. There remain substantial contradictions, uncertainties, and sensitivity to assumptions between the different methods commonly used. Yet providing decision-relevant downscaled climate projections to help support national and local adaptation is core to the growing global momentum seeking to operationalize what is, in effect, still foundational research. We argue that any downscaled climate information must address the criteria of being plausible, defensible and actionable. Climate scientists cannot absolve themselves of their ethical responsibility when informing adaptation and must, therefore, be diligent in ensuring any information provided adequately addresses these three criteria. Frameworks for supporting such assessment are not well developed. We interrogate the conceptual foundations of statistical downscaling methodologies and their assumptions, and articulate a framework for evaluating and integrating downscaling output into the wider landscape of climate information. For ESD there are key criteria that need to be satisfied to underpin the credibility of the derived product. Assessing these criteria requires the use of appropriate metrics to test the comprehensive treatment of local climate response to large-scale forcing, and to compare across methods. We illustrate the potential consequences of methodological choices on the interpretation of downscaling results and explore the purposes, benefits and limitations of using statistical downscaling.     

Relationships between cut-off lows and the semiannual and southern oscillations

The characteristics of Southern Cut-off Lows (CoLs) are studied for the period 1979–2008. The systematic identification of CoLs is realized by applying an original automated scheme using mean daily geopotential height and air temperature at 500?hPa NCEP-DOE II Reanalysis data. From closed lows’ trajectories established from the Equator to the polar jet stream, extratropical lows are analyzed and the stage of cut-off is defined as a secluded low presenting a cold core. From 4,843 cases the general CoL features are presented and confirm several previous results such as the geographic distribution which shows that they are more frequent in the latitudinal band contained between 20°S and 45°S and in close proximity to the continents. On a seasonal time scale, CoLs are more numerous from late summer to autumn, with a maximum of frequency in March/April. In winter (June–July–August), they are fewer but deeper than during the rest of the year. In the median domain (~32.5°S), the annual cycle of the frequency is bimodal and present two peaks during transitional seasons. In this zone, the seasonal cycle varies in accordance with the Semiannual Oscillation. Thereby, when the meridional gradient of temperature/pressure is reinforced between mid and high latitudes, CoLs are more frequent in the median domain. Over the period 1979–2008, the annual CoLs’ frequency exhibits a positive trend of about 25%. This increase is associated with a widening of the latitudinal domain of occurrence equatorward as well as poleward. The trend is linked with an abrupt positive shift in the number of CoLs’ generation between 1998 and 1999. The geographical distribution of CoLs frequency varies significantly in accordance with El Ni?o Southern Oscillation with more CoL’s at lower (higher) latitudes during La Ni?a (El Ni?o) events, principally in the Southern Pacific.     

GNSS receiver autonomous integrity monitoring (RAIM) performance analysis

The availability of GPS signals is a major concern for many existing and potential applications. Fortunately, with the development of Galileo by the European Commission (EC) and European Space Agency (ESA) and new funding for the restoration of the Russian GLONASS announced by the Russian Federation (Revnivykh et al., in European Navigation Conference 2005, Munich, Germany, July 19–22), the future for satellite-based positioning and navigation applications is extremely promising. With the complete cooperation from all these global navigation satellite systems (GNSS), greater levels of satellite visibility and therefore integrity can be expected. In this paper, a receiver autonomous integrity monitoring (RAIM) scheme along with reliability and separability measures are used to assess integrity performance levels of standalone GPS and integrated GPS/GLONASS, GPS/Galileo and GPS/GLONASS/Galileo systems where the clock offsets for each of the additional systems are estimated. It is shown, herein, that a minimum of three satellites must be visible in an additional system in order to provide a full integrity contribution when the system’s clock offset is to be estimated within the adjustment. A comparison of the integrity results obtained via system clock offsets estimated in the adjustment versus the case where the offsets are known and the measurements are corrected prior to the adjustment is also made for a high elevation mask scenario. Global simulation results for combined GPS/GLONASS/Galileo show that, theoretically, for the time of simulation and for any point on the globe, an outlier of 20 m can be detected with 80% probability at the 0.5% significance level and then separated from any other measurement with 90% probability. Corresponding values for the GPS only and combined GPS/GLONASS and GPS/Galileo systems, respectively, are approximately 435, 110 and 28 m, respectively, for the maximum MSBs and 312, 50 and 26 m, respectively, for the maximum MDBs. Temporal 24 h simulations for the GPS/GLONASS/Galileo scenario delivered agreeable results with the global snapshots for a 15° elevation mask. For the case where system clock offsets are estimated within the adjustment, it was shown that only the reliability measure was available for 100% of the time, with horizontal external reliability values of no more than about 12 m when a 30° masking angle was used. By assuming the clock offsets were determined and corrected for prior to the adjustment, the separability measure was markedly improved and was also available 100% of the time.     

MM5 simulations of interannual change and the diurnal cycle of southern African regional climate

Summary Two cumulus convection and two planetary boundary layer schemes are used to investigate the climate of southern Africa using the MM5 regional climate model. Both a wet (1988/89) and a dry (1991/92) summer (December–February, DJF) rainfall season are simulated and the results compared with three different observational sources: Climate Research Unit seasonal data (precipitation, 2 m surface temperature, number of rain days), satellite-derived diurnal precipitation and the Surface Radiation Budget diurnal short-wave fluxes and optical depth. Using the ETA model boundary layer in MM5 simulates too much incident short-wave radiation at the surface at 12 UTC, whereas the medium range forecast model boundary layer yields a diurnal cycle of short-wave radiation closer to the observed. The Betts-Miller convection scheme in MM5 simulates peak rainfall later in the day and less rain days than observed, whereas when using the Kain-Fritsch convection scheme a peak rainfall earlier in the day and more rain days than observed are simulated. The intensity of the hydrological cycle is therefore dependent on the choice of convection scheme, which in turn is further modified by the boundary layer scheme. Precipitation during the wet 1988/89 season is reasonably captured by most simulations, though using the Betts-Miller scheme more accurately simulates rainfall during the dry 1991/92 season. Mean DJF biases in the surface temperature and diurnal temperature range are consistent with biases in the number of rain days and the diurnal cycles of surface moisture and energy.