There are well-known difficulties to run numerical weather prediction (NWP) and climate models at resolutions traditionally referred to as ‘grey-zone’ ( 3 8 km) where deep convection is neither completely resolved by the model dynamics nor completely subgrid. In this study, we describe the performance of an operational NWP model, HARMONIE, in a climate setting (HCLIM), run at two different reso...

We report on the retrieval of directional sea-roughness (the full directional mean square slope, including direction and isotropy) through inversion of Global Navigation Satellite System Reflections (GNSS-R) data collected during an experimental flight at 1 km altitude. The emphasis is on the utilization of the entire Delay-Doppler Map (DDM) in order to infer ocean roughness directional paramet...

We describe the remapped particle-mesh method, a new mass-conserving method for solving the density equation which is suitable for combining with semi-Lagrangian methods for compressible flow applied to numerical weather prediction. In addition to the conservation property, the remapped particle-mesh method is computationally efficient and at least as accurate as current semi-Lagrangian methods...

The lack of adequate tropospheric observations over marine areas adversely affects the forecast skill of numerical weather prediction systems, and can therefore pose a threat to fleet operations. Clearly, space-based remote sensors must be employed to derive high-quality observations to help fill these data voids. In addition, it is important to marry these data with assimilation systems that c...

The accuracy of numerical weather forecasts is crucial in many engineering applications, especially for the management of renewable energy. In this paper, we give a short overview of methods used to improve local weather forecast. Then we propose a new state space model in order to correct bias and phase errors in numerical wind forecasts. We present some results for real life data.

We have seen in a recent paper (Surcel et al., 2009) that the diurnal cycle of precipitation over the continental US exhibits some seasonal variability. This is a consequence of the fact that during the summer, precipitation is strongly forced by the diurnal cycle of solar heating and it usually initiates as small scales, while during spring, precipitation occurs at larger scales, being synopti...

Modern troposphere delay models like the Vienna Mapping Functions (VMF1) are based on data from Numerical Weather Models (NWM) with a time resolution of typically 6 hours. Different from purely analytical formulations like the Global Mapping Functions, the VMF1 can account for real weather phenomena like changing high and low pressure systems and are thus more accurate. Additionally, the zenith...

This paper presents an interesting comparative study between a fast radiative transfer model (RTTOV) and a reference (line by line) model (ARTS) for the high altitude channels 19-22 of SSMIS. The simulations have been performed using globally distributed numerical weather prediction model profiles from MetOffice. One of the main problems present in the study is that these atmospheric profiles o...

InSAR signal delays due to the varying atmospheric refractivity are a potential data source to improve weather models [1]. Especially with the launch of the new Sentinel-1 satellites, which increases data coverage, latency and accessibility, it may become possible to operationalize the assimilation of differential integrated refractivity (DIR) values in numerical weather models. Although studie...

Logistic models are studied as a tool to convert output from numerical weather forecasting systems (deterministic and ensemble) into probability forecasts for binary events. A logistic model obtains by putting the logarithmic odds ratio equal to a linear combination of the inputs. As any statistical model, logistic models will suffer from over-fitting if the number of inputs is comparable to th...