Improving the precipitation accumulation analysis using lightning measurements and different integration periods

Gregow, Erik; Pessi, Antti; Mäkelä, Antti; Saltikoff, Elena

doi:10.5194/hess-21-267-2017

Cited by 3 publications

(4 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hourly radar reflectivity images from the weather radar network of the Finnish Meteorological Institute (FMI, Saltikoff et al, 2010;Gregow et al, 2017) were used to preliminary identify the sea-effect snow case on 8 January 2016. Moreover, radar-based hourly accumulated precipitation images were qualitatively compared to simulations of precipitation with a weather prediction model (HARMONIE; see below).…”

Section: Methodsmentioning

confidence: 99%

Intense sea-effect snowfall case on the western coast of Finland

et al. 2017

View full text Add to dashboard Cite

Abstract.A new national daily snowfall record was measured in Finland on 8 January 2016 when it snowed 73 cm (31 mm as liquid water) in less than a day in Merikarvia on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and to qualitatively estimate the performance of HARMONIE, a non-hydrostatic convection-permitting weather prediction model, in simulating the spatial and temporal evolution of the snowbands. The model simulation, including data assimilation, was run at 2.5 km horizontal resolution and 65 levels in vertical. HARMONIE was found to capture the overall sea-effect snowfall situation quite well, as both the timing and the location of the most intense snowstorm were properly simulated. Based on our preliminary analysis, the snowband case was triggered by atmospheric instability above the mostly ice-free sea and a low-level convergence zone almost perpendicular to the coastline. The simulated convective available potential energy (CAPE) reached a value of 87 J kg −1 near the site of the observed snowfall record.

show abstract

Section: Methodsmentioning

confidence: 99%

Intense sea-effect snowfall case on the western coast of Finland

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The analysis systems are able to process several types of in situ and remotely-sensed observations: Synop, METAR (Meteorological Aerodrome Reports), road weather observations, soundings, air-traffic observations, weather radar radial winds and reflectivity, and Meteosat9 satellite data (Gregow et al, 2017).…”

Section: The Local Analysis and Prediction System -Laps/lepsmentioning

confidence: 99%

“…The quality of the analysis depends on observation networks (especially on remote sensing data) in which their availability, in both space and time, is essential. The analysis systems are able to process several types of in situ and remotely‐sensed observations: Synop, METAR (Meteorological Aerodrome Reports), road weather observations, soundings, air‐traffic observations, weather radar radial winds and reflectivity, and Meteosat9 satellite data (Gregow et al, 2017).…”

Section: Datasetsmentioning

confidence: 99%

Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations

Filioglou

Preißler²,

Troiville³

et al. 2022

Meteorological Applications

Self Cite

View full text Add to dashboard Cite

Wind information in urban areas is essential for many applications related to air pollution, urban climate and planning, safety of drone-related operations, and assessment of urban wind energy potential. These applications require accurate wind forecasts, and obtaining this information in an urban environment is challenging as the morphology of a city varies from street to street, altering the wind flow. Remote sensing techniques such as Doppler lidars (light detection and ranging) provide a unique opportunity for wind forecast verification as they can provide both the vertical profile of the horizontal wind and the spatial variation in the horizontal domain at high resolution. In this study, the performance of numerical weather prediction (NWP) models, analysis systems, and large-eddy simulation (LES) models have been analysed by comparing the modelled winds against Doppler lidar observations under various atmospheric conditions and from season to season, in the coastal environment of Helsinki, Finland. The long-term mean vertical profile of the modelled horizontal wind shows good agreement with observations; the NWP model and the analysis systems selected here exhibit different strengths and weaknesses depending on the atmospheric conditions but no significant diurnal variation in performance. However, both the model and analysis systems show differences in their spatially-averaged bias when investigating different wind directions. LES verification shows that these models can potentially provide winds down to Associated post doc with Vaisala through PoDoCo program.

show abstract

“…The HLAPS is a hurricane version of diagnostic tool widely used for short-range storm forecasting through wet atmospheric simulations; it eliminates the model spin-up problem and exhibits high computational efficiency [30]. The original LAPS has often been utilized quite successfully for very short-range forecasts of severe weather, such as strong wind and precipitation [31][32][33][34][35][36][37][38]. In this one-way hybrid system, the HLAPS was used to analyze the model first-guess as a "meteorological assimilation system".…”

Section: Hurricane Local Analysis and Prediction Systemmentioning

confidence: 99%

The Impact of Assimilating Winds Observed during a Tropical Cyclone on a Forecasting Model

et al. 2022

View full text Add to dashboard Cite

The accurate and timely depiction of the state of severe weather is critical for enhancing forecaster situational awareness. This study attempted to develop a hurricane forecasting model with a warm-start run and investigated the impact of winds observed during a tropical cyclone on long-term lead times. The Hurricane Research System initialized with the Hurricane Local Analysis Prediction System (HRS/HLAPS) was applied to Hurricanes Katrina and Dennis (2005). The forecasting model used a warm-start run with 7% improved wind data and cloud initialization using the HLAPS. The simulated cyclones were more intense and realistic structures, although the performance varied slightly according to the lead time and cyclone characteristics. The results show that the tropical cyclone development (track and intensity) was significantly affected by initial forcing up to 6–12 h, as well as by the forcing of the limit condition after 6 h. The well-organized spiral bands of convective precipitations were also captured, particularly within the 6 h spin-up time due to vertical wind shear and water vapor trapped in the lower atmosphere. This study demonstrates that aircraft-observed winds and convective initialization can be useful for numerical modeling and operational forecasting.

show abstract

Improving the precipitation accumulation analysis using lightning measurements and different integration periods

Cited by 3 publications

References 25 publications

Intense sea-effect snowfall case on the western coast of Finland

Intense sea-effect snowfall case on the western coast of Finland

Evaluating modelled winds over an urban area using ground‐based Doppler lidar observations

The Impact of Assimilating Winds Observed during a Tropical Cyclone on a Forecasting Model

Contact Info

Product

Resources

About