Using operational weather radar to assess high-resolution numerical weather prediction over the British Isles for a cold air outbreak case-study

2013 ◽  
Vol 140 (678) ◽  
pp. 225-239 ◽  
Author(s):  
K. McBeath ◽  
P. R. Field ◽  
R. J. Cotton
Keyword(s):  
High Resolution ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Weather Radar ◽  
British Isles ◽  
Cold Air ◽  
Numerical Weather ◽  
Cold Air Outbreak ◽  
Outbreak Case

scholarly journals Assessment of valley cold pools and clouds in a very high-resolution numerical weather prediction model

2015 ◽  
Vol 8 (10) ◽  
pp. 3105-3117 ◽  
Author(s):  
J. K. Hughes ◽  
A. N. Ross ◽  
S. B. Vosper ◽  
A. P. Lock ◽  
B. C. Jemmett-Smith
Keyword(s):  
High Resolution ◽  
Relative Humidity ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Wave Radiation ◽  
Cold Pool ◽  
Cold Air ◽  
Numerical Weather ◽  
Pool Formation ◽  
Very High

Abstract. The formation of cold air pools in valleys under stable conditions represents an important challenge for numerical weather prediction (NWP). The challenge is increased when the valleys that dominate cold pool formation are on scales unresolved by NWP models, which can lead to substantial local errors in temperature forecasts. In this study a 2-month simulation is presented using a nested model configuration with a finest horizontal grid spacing of 100 m. The simulation is compared with observations from the recent COLd air Pooling Experiment (COLPEX) project and the model's ability to represent cold pool formation, and the surface energy balance is assessed. The results reveal a bias in the model long-wave radiation that results from the assumptions made about the sub-grid variability in humidity in the cloud parametrization scheme. The cloud scheme assumes relative humidity thresholds below 100 % to diagnose partial cloudiness, an approach common to schemes used in many other models. The biases in radiation, and resulting biases in screen temperature and cold pool properties are shown to be sensitive to the choice of critical relative humidity, suggesting that this is a key area that should be improved for very high-resolution modeling.

Physics, Resolution and Data Assimilation: Making sense of Greenland climate and ice sheet Surface Mass Balance with HARMONIE Climate

2021 ◽  
Author(s):  
Ruth Mottram ◽  
Oskar Landgren ◽  
Rasmus Anker Pedersen ◽  
Kristian Pagh Nielsen ◽  
Ole Bøssing Christensen ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Climate Model ◽  
Weather Prediction ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass ◽  
Mass Budget ◽  
Numerical Weather

<p>The development of the HARMONIE model system has led to huge advances in numerical weather prediction, including over Greenland where a numerical weather prediction (NWP) model is used to forecast daily surface mass budget over the Greenland ice sheet as presented on polarportal.dk. The new high resolution Copernicus Arctic Reanalysis further developed the possibilities in HARMONIE with full 3DVar data assimilation and extended use of quality-controlled local observations. Here, we discuss the development and current status of the climate version of the HARMONIE Climate model (HCLIM). The HCLIM system has opened up the possibility for flexible use of the model at a range of spatial scales using different physical schemes including HARMONIE-AROME, ALADIN and ALARO for different spatial and temporal resolutions and assimilating observations, including satellite data on sea ice concentration from ESA CCI+, to improve hindcasts. However, the range of possibilities means that documenting the effects of different physics and parameterisation schemes is important before widespread application. </p><p>Here, we focus on HCLIM performance over the Greenland ice sheet, using observations to verify the different plausible set-ups and investigate biases in climate model outputs that affect the surface mass budget (SMB) of the Greenland ice sheet. </p><p>The recently funded Horizon 2020 project PolarRES will use the HCLIM model for very high resolution regional downscaling, together with other regional climate models in both Arctic and Antarctic regions, and our analysis thus helps to optimise the use of HCLIM in the polar regions for different modelling purposes.</p>

Objective 3D atmospheric front detection in high-resolution numerical weather prediction data

2021 ◽  
Author(s):  
Andreas Beckert ◽  
Lea Eisenstein ◽  
Tim Hewson ◽  
George C. Craig ◽  
Marc Rautenhaus
Keyword(s):  
High Resolution ◽  
Numerical Weather Prediction ◽  
Feature Detection ◽  
3D Visualization ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Detection Methods ◽  
Numerical Weather ◽  
Atmospheric Fronts ◽  
Front Detection

<p><span>Atmospheric fronts, a widely used conceptual model in meteorology, describe sharp boundaries between two air masses of different thermal properties. In the mid-latitudes, these sharp boundaries are commonly associated with extratropical cyclones. The passage of a frontal system is accompanied by significant weather changes, and therefore fronts are of particular interest in weather forecasting. Over the past decades, several two-dimensional, horizontal feature detection methods to objectively identify atmospheric fronts in numerical weather prediction (NWP) data were proposed in the literature (e.g. Hewson, Met.Apps. 1998). In addition, recent research (Kern et al., IEEE Trans. Visual. Comput. Graphics, 2019) has shown the feasibility of detecting atmospheric fronts as three-dimensional surfaces representing the full 3D frontal structure. In our work, we build on the studies by Hewson (1998) and Kern et al. (2019) to make front detection usable for forecasting purposes in an interactive 3D visualization environment. We consider the following aspects: (a) As NWP models evolved in recent years to resolve atmospheric processes on scales far smaller than the scale of midlatitude-cyclone- fronts, we evaluate whether previously developed detection methods are still capable to detect fronts in current high-resolution NWP data. (b) We present integration of our implementation into the open-source “Met.3D” software (http://met3d.wavestoweather.de) and analyze two- and three-dimensional frontal structures in selected cases of European winter storms, comparing different models and model resolution. (c) The considered front detection methods rely on threshold parameters, which mostly refer to the magnitude of the thermal gradient within the adjacent frontal zone - the frontal strength. If the frontal strength exceeds the threshold, a so-called feature candidate is classified as a front, while others are discarded. If a single, fixed, threshold is used, unwanted “holes” can be observed in the detected fronts. Hence, we use transparency mapping with fuzzy thresholds to generate continuous frontal features. We pay particular attention to the adjustment of filter thresholds and evaluate the dependence of thresholds and resolution of the underlying data.</span></p>

Evaluation of a high-resolution numerical weather prediction model's simulated clouds using observations from CloudSat, GOES-13 and in situ aircraft

2018 ◽  
Vol 144 (715) ◽  
pp. 1681-1694 ◽  
Author(s):  
Zhipeng Qu ◽  
Howard W. Barker ◽  
Alexei V. Korolev ◽  
Jason A. Milbrandt ◽  
Ivan Heckman ◽  
...  
Keyword(s):  
High Resolution ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Numerical Weather
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