Search results for "Numerical Weather Prediction"

2021

Abstract. The formation of ice in clouds is an important processes in mixed-phase and ice-phase clouds. Yet, the representation of ice formation in numerical models is highly uncertain. In the last decade, several new parameterizations for heterogeneous freezing have been proposed. However, it is currently unclear what the effect of choosing one parameterization over another is in the context of numerical weather prediction. We conducted high-resolution simulations (Δx=250 m) of moderately deep convective clouds (cloud top ∼-18 ∘C) over the southwestern United Kingdom using several formulations of ice formation and compared the resulting changes in cloud field properties to the spread of an…

Sea breeze thunderstorms in the eastern Iberian Peninsula. Neighborhood verification of HIRLAM and HARMONIE precipitation forecasts

2014

In this study we investigated sea breeze thunderstorms with intense convective activity (i.e., heavy rainfall, hail and gusty winds) that occurred over the eastern Iberian Peninsula (Spain) and were missed by the operational HIRLAM model. We used two grid-spacing setups (5.0. km and 2.5. km) of the hydrostatic HIRLAM model, and the non-hydrostatic spectral HARMONIE suite (2.5. km), to simulate isolated convection associated with sea breezes. The overall aim is to estimate the ability of these three experimental setups, in particular the HARMONIE model as the forthcoming operational numerical weather prediction in most European Weather Services, to correctly simulate convective precipitation…

Classification of precipitation events with a convective response timescale and their forecasting characteristics

2011

[1] The convective timescale τc, which is mainly determined by the ratio of CAPE and precipitation rate, provides a physically-based measure to distinguish equilibrium and non-equilibrium convection. A statistical analysis of this timescale, based upon observational data from radiosonde ascents, rain gauges, and radar for seven warm seasons in Germany, reveals that the equilibrium and non-equilibrium regimes can be regarded as extremes of a continuous distribution. The two regimes characterize very different interactions between the large-scale flow and convection. The quality of precipitation forecasts from a non-hydrostatic regional weather prediction model with parameterized convection d…

Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Re…

2021

The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partiti…

Transfer Learning with Convolutional Networks for Atmospheric Parameter Retrieval

2018

The Infrared Atmospheric Sounding Interferometer (IASI) on board the MetOp satellite series provides important measurements for Numerical Weather Prediction (NWP). Retrieving accurate atmospheric parameters from the raw data provided by IASI is a large challenge, but necessary in order to use the data in NWP models. Statistical models performance is compromised because of the extremely high spectral dimensionality and the high number of variables to be predicted simultaneously across the atmospheric column. All this poses a challenge for selecting and studying optimal models and processing schemes. Earlier work has shown non-linear models such as kernel methods and neural networks perform w…

Simulation of surface energy fluxes and meteorological variables using the Regional Atmospheric Modeling System (RAMS): Evaluating the impact of land…

2018

Atmospheric mesoscale numerical models are commonly used not only for research and air quality studies, but also for other related applications, such as short-term weather forecasting for atmospheric, hydrological, agricultural and ecological modelling. A key element to produce faithful simulations is the proper representation of the soil parameters used in the initialization of the corresponding mesoscale numerical model. The Regional Atmospheric Modeling System (RAMS) is used in the current study. The model code has been updated in order to permit the model to be initialized using a heterogeneous soil moisture and temperature distribution derived from land surface models. Particularly, RA…

Impact of Initial Soil Temperature Derived from Remote Sensing and Numerical Weather Prediction Datasets on the Simulation of Extreme Heat Events

2016

Extreme heat weather events have received increasing attention and has become of special importance as they can remarkably affect sectors as diverse as public health, energy consumption, water resources, natural biodiversity and agricultural production. In this regard, summer temperatures have become a parameter of essential interest under a framework of a hypothetical increase in the number of intense-heat conditions. Thus, their forecast is a crucial aspect bearing in mind a mitigation of the effects and impacts that these intense-heat situations could produce. The current work tries to reach a better understanding of these sorts of situations that are really common over the Western Medit…

Implementation of non-local boundary layer schemes in the Regional Atmospheric Modeling System and its impact on simulated mesoscale circulations

2016

This paper proposes the implementation of different non-local Planetary Boundary Layer schemes within the Regional Atmospheric Modeling System (RAMS) model. The two selected PBL parameterizations are the Medium-Range Forecast (MRF) PBL and its updated version, known as the Yonsei University (YSU) PBL. YSU is a first-order scheme that uses non-local eddy diffusivity coefficients to compute turbulent fluxes. It is based on the MRF, and improves it with an explicit treatment of the entrainment. With the aim of evaluating the RAMS results for these PBL parameterizations, a series of numerical simulations have been performed and contrasted with the results obtained using the Mellor and Yamada (M…

Life Cycle Study of a Diabatic Rossby Wave as a Precursor to Rapid Cyclogenesis in the North Atlantic—Dynamics and Forecast Performance

2011

Monthly Weather Review, 139 (6)

Aircraft type-specific errors in AMDAR weather reports from commercial aircraft

2008

AMDAR (Aircraft Meteorological DAta Relay) automated weather reports from commercial aircraft provide an increasing amount of input data for numerical weather prediction models. Previous studies have investigated the quality of AMDAR data. Few of these studies, however, have revealed indications of systematic errors dependent upon the aircraft type. Since different airlines use different algorithms to generate AMDAR reports, it has remained unclear whether a dependency on the aircraft type is caused by physical properties of the aircraft or by different data processing algorithms. In the present study, a special AMDAR dataset was used to investigate the physical type-dependent errors of AMD…