Forecasting auroras from regional and global magnetic field measurements

Abstract. We use the connection between auroral sightings and rapid geomagnetic field variations in a concept for a Regional Auroral Forecast (RAF) service. The service is based on statistical relationships between near-real-time alerts issued by the NOAA Space Weather Prediction Center and magnetic time derivative (dB∕dt) values measured by five MIRACLE magnetometer stations located in Finland at auroral and sub-auroral latitudes. Our database contains NOAA alerts and dB∕dt observations from the years 2002–2012. These data are used to create a set of conditional probabilities, which tell the service user when the probability of seeing auroras exceeds the average conditions in Fennoscandia during the coming 0–12 h. Favourable conditions for auroral displays are associated with ground magnetic field time derivative values (dB∕dt) exceeding certain latitude-dependent threshold values. Our statistical analyses reveal that the probabilities of recording dB∕dt exceeding the thresholds stay below 50 % after NOAA alerts on X-ray bursts or on energetic particle flux enhancements. Therefore, those alerts are not very useful for auroral forecasts if we want to keep the number of false alarms low. However, NOAA alerts on global geomagnetic storms (characterized with Kp values  >  4) enable probability estimates of >  50 % with lead times of 3–12 h. RAF forecasts thus rely heavily on the well-known fact that bright auroras appear during geomagnetic storms. The additional new piece of information which RAF brings to the previous picture is the knowledge on typical storm durations at different latitudes. For example, the service users south of the Arctic Circle will learn that after a NOAA ALTK06 issuance in night, auroral spotting should be done within 12 h after the alert, while at higher latitudes conditions can remain favourable during the next night.

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Forecasting auroras from regional and global magnetic field measurements

10.5194/gi-2015-33 ◽

2016 ◽

Author(s):

K. Kauristie ◽

M. Myllys ◽

N. Partamies ◽

A. Viljanen ◽

P. Peitso ◽

...

Keyword(s):

Magnetic Field ◽

Geomagnetic Storms ◽

Time Derivative ◽

Field Measurements ◽

False Alarms ◽

Research Station ◽

Time Data ◽

Number Of False Alarms ◽

Northern Fennoscandia ◽

Probability Estimates

Abstract. We present a concept for a Regional Auroral Forecast service (RAF), which uses near-real-time data from the IMAGE network of ground-based magnetometers operated in Northern Fennoscandia. Performance of RAF is demonstrated in a case study with auroral recordings from the Sodankylä research station. RAF is based on archived National Oceanic and Atmospheric Administration (NOAA) space weather alerts and regional magnetic field recordings (years 2002–2012). The archives are used to create a set of conditional probabilities, which tell the service user when the probability to see auroras exceeds the average conditions in Fennoscandia during the coming 0–12 hours. Favourable conditions for auroral displays are associated with ground magnetic field time derivative values (dB/dt) exceeding certain latitude dependent threshold values. Our statistical analyses reveal that the probabilities to record dB/dt exceeding the thresholds stay below 50% after NOAA alerts on X-ray bursts or on energetic particle flux enhancements. Therefore, those alerts are not very useful for auroral forecasts, if we want to keep the number of false alarms low. However, NOAA alerts on global geomagnetic storms (characterized with Kp values >4) enable probability estimates of >50% with lead times of 3–12 hours. RAF forecasts thus rely heavily on the well-known fact that bright auroras appear during geomagnetic storms. The additional new piece of information which RAF brings to the previous picture is the knowledge on typical storm durations at different latitudes. For example, the service users south of the Artic Circle will learn that after a NOAA ALTK06 issuance in night, auroral spotting should be done within 12 hours after the alert, while at higher latitudes conditions can remain favourable during the next night.

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Coupling ensemble weather predictions based on TIGGE database with Grid-Xinanjiang model for flood forecast

Advances in Geosciences ◽

10.5194/adgeo-29-61-2011 ◽

2011 ◽

Vol 29 ◽

pp. 61-67 ◽

Cited By ~ 35

Author(s):

H.-J. Bao ◽

L.-N. Zhao ◽

Y. He ◽

Z.-J. Li ◽

F. Wetterhall ◽

...

Keyword(s):

Weather Prediction ◽

Grid Cell ◽

Flood Forecasting ◽

False Alarms ◽

Flood Forecast ◽

Distributed Hydrological Model ◽

Xinanjiang Model ◽

Numerical Weather ◽

Number Of False Alarms ◽

Promising Tool

Abstract. The incorporation of numerical weather predictions (NWP) into a flood forecasting system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and lead to a high number of false alarms. The availability of global ensemble numerical weather prediction systems through the THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for flood forecast. The Grid-Xinanjiang distributed hydrological model, which is based on the Xinanjiang model theory and the topographical information of each grid cell extracted from the Digital Elevation Model (DEM), is coupled with ensemble weather predictions based on the TIGGE database (CMC, CMA, ECWMF, UKMO, NCEP) for flood forecast. This paper presents a case study using the coupled flood forecasting model on the Xixian catchment (a drainage area of 8826 km2) located in Henan province, China. A probabilistic discharge is provided as the end product of flood forecast. Results show that the association of the Grid-Xinanjiang model and the TIGGE database gives a promising tool for an early warning of flood events several days ahead.

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Improvement of mesoscale numerical weather prediction WRF-ARW in the Republic of Belarus by assimilation of radar wind and reflectivity data

Journal of the Belarusian State University. Geography and Geology ◽

10.33581/2521-6740-2020-2-3-13 ◽

2020 ◽

pp. 3-13

Author(s):

Palina A. Zaiko ◽

Aliaksandr N. Krasouski ◽

Siarhei K. Barodka

Keyword(s):

Mesoscale Model ◽

Forecast Error ◽

Weather Prediction ◽

Three Dimensional ◽

Wrf Model ◽

Radar Data ◽

False Alarms ◽

Strong Wind ◽

Number Of False Alarms ◽

Circulation Types

The forecasts of severe weather events obtained with the WRF numerical mesoscale model with the adapted system for assimilation of reflectivity and radial velocity data from the network of Belarusian Doppler weather radars used in Belhydromet in 2019 are analysed. A description of the system for the echo quality control based on the radar dual-polarisation characteristics and the method for three-dimensional variational assimilation (3D-VAR) used to assimilate data in the WRF model are described. The results of case studies on the simulation of precipitation and strong wind for various circulation types in Belarus with and without radar data assimilation are given. The statistical and object-oriented verification of these forecasts is provided. The results of the comprehensive assessment reveal a decrease in the forecast error for 10-m wind speed for the early forecast hours (+6 h) by 1.34 m/s, as well as a more accurate forecast of the location, orientation of the cloud systems and precipitation zones, and a decrease in the number of false alarms in the version with assimilation. A preliminary conclusion on the possibility of using the forecast results in nowcasting systems is also made.

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