The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region

Haiden, Thomas; Kann, Alexander; Wittmann, Christoph; Pistotnik, Georg; Bica, Benedikt; Gruber, Christine

doi:10.1175/2010waf2222451.1

Cited by 265 publications

(228 citation statements)

References 33 publications

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“…The upper-level verification is achieved using ECMWF analyses reference data at four pressure levels: 925, 850, 700, and 500 hPa, which are adapted to the model resolutions of both AROME-EPS and ALADIN-LAEF. The evaluation of precipitation forecasts is performed using the very high-resolution precipitation analyses of the ZAMG nowcasting system INCA (Integrated Nowcasting through Comprehensive Analyses; Haiden et al, 2011). This is necessary as the average station distance of precipitation observations is too large to resolve the fine spatial structures of precipitation events.…”

Section: Verification Datamentioning

confidence: 99%

“…INCA blends data from automatic weather stations, remote sensing data (radar, satellite), forecast fields of numerical weather prediction (NWP) models, and high-resolution topographic data (Haiden et al, 2011). It provides hourly 3-D fields of temperature, humidity, wind, and 2-D fields of cloudiness, precipitation rate, and precipitation type with an update frequency of 15 min to 1 h. The precipitation analyses are provided for different accumulation periods.…”

Section: Verification Datamentioning

confidence: 99%

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On the forecast skill of a convection-permitting ensemble

Schellander-Gorgas¹,

Wang²,

Meier³

et al. 2017

Geosci. Model Dev.

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Abstract. The 2.5 km convection-permitting (CP) ensemble AROME-EPS (Applications of Research to Operations at Mesoscale -Ensemble Prediction System) is evaluated by comparison with the regional 11 km ensemble ALADIN-LAEF (Aire Limitée Adaption dynamique Développement InterNational -Limited Area Ensemble Forecasting) to show whether a benefit is provided by a CP EPS. The evaluation focuses on the abilities of the ensembles to quantitatively predict precipitation during a 3-month convective summer period over areas consisting of mountains and lowlands. The statistical verification uses surface observations and 1 km × 1 km precipitation analyses, and the verification scores involve state-of-the-art statistical measures for deterministic and probabilistic forecasts as well as novel spatial verification methods. The results show that the convectionpermitting ensemble with higher-resolution AROME-EPS outperforms its mesoscale counterpart ALADIN-LAEF for precipitation forecasts. The positive impact is larger for the mountainous areas than for the lowlands. In particular, the diurnal precipitation cycle is improved in AROME-EPS, which leads to a significant improvement of scores at the concerned times of day (up to approximately one-third of the scored verification measure). Moreover, there are advantages for higher precipitation thresholds at small spatial scales, which are due to the improved simulation of the spatial structure of precipitation.

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Section: Verification Datamentioning

confidence: 99%

Section: Verification Datamentioning

confidence: 99%

On the forecast skill of a convection-permitting ensemble

Schellander-Gorgas¹,

Wang²,

Meier³

et al. 2017

Geosci. Model Dev.

View full text Add to dashboard Cite

show abstract

“…Global radiation, air temperature, air humidity and wind speed were measured at a reference station located at DFS 39 km 47 • 16 11.055 N, 16 • 13 47.892 E, 300 m a.s.l. To link the measured microscale meteorological data to mesoscale meteorological data, a systematic intercomparison between the local meteorological stations of the Austrian Weather Service (ZAMG) and the 1 × 1 km gridded observational data set INCA (Haiden et al, 2011) was made. Since the local permanent meteorological stations of ZAMG were used to produce the gridded INCA data set, they are highly consistent.…”

Section: Preparation Of Input 231 Meteorological Inputmentioning

confidence: 99%

“…The RCMs were bias corrected using the quantile mapping technique (Déqué, 2007) based on the E-OBS data set (Haylock et al, 2008) and scaled. In a second step, the data were spatially localized to a 1 km × 1 km grid encompassing the area under investigation using the Austrian INCA data set (Haiden et al, 2011). In a third step, the data were temporally disaggregated from a resolution of 1 day to 1 h. Temperature was disaggregated based on the daily maximum and minimum temperatures using three piecewise continuous cosine curves (Koutsoyiannis, 2003;Goler and Formayer, 2012).…”

Section: Preparation Of Input 231 Meteorological Inputmentioning

confidence: 99%

Can riparian vegetation shade mitigate the expected rise in stream temperatures due to climate change during heat waves in a human-impacted pre-alpine river?

Trimmel

Weihs

Leidinger

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Global warming has already affected European rivers and their aquatic biota, and climate models predict an increase of temperature in central Europe over all seasons. We simulated the influence of expected changes in heat wave intensity during the 21st century on water temperatures of a heavily impacted pre-alpine Austrian river and analysed future mitigating effects of riparian vegetation shade on radiant and turbulent energy fluxes using the deterministic Heat Source model. Modelled stream water temperature increased less than 1.5 • C within the first half of the century. Until 2100, a more significant increase of around 3 • C in minimum, maximum and mean stream temperatures was predicted for a 20-year return period heat event. The result showed clearly that in a highly altered river system riparian vegetation was not able to fully mitigate the predicted temperature rise caused by climate change but would be able to reduce water temperature by 1 to 2 • C. The removal of riparian vegetation amplified stream temperature increases. Maximum stream temperatures could increase by more than 4 • C even in annual heat events. Such a dramatic water temperature shift of some degrees, especially in summer, would indicate a total shift of aquatic biodiversity. The results demonstrate that effective river restoration and mitigation require re-establishing riparian vegetation and emphasize the importance of land-water interfaces and their ecological functioning in aquatic environments.

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“…For details on meteorological observation methods and related uncertainties the interested reader is referred to Haiden et al (2011).…”

Section: Measurementsmentioning

confidence: 99%

The Austrian radiation monitoring network ARAD – best practice and added value

et al. 2016

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Abstract. The Austrian RADiation monitoring network (ARAD) has been established to advance the national climate monitoring and to support satellite retrieval, atmospheric modeling and the development of solar energy techniques. Measurements cover the downward solar and thermal infrared radiation using instruments according to Baseline Surface Radiation Network (BSRN) standards. A unique feature of ARAD is its vertical dimension of five stations, covering an altitude range between about 200 m a.s.l (Vienna) and 3100 m a.s.l. (BSRN site Sonnblick). The paper outlines the aims and scopes of ARAD, its measurement and calibration standards, methods, strategies and station locations. ARAD network operation uses innovative data processing for quality assurance and quality control, utilizing manual and automated control algorithms. A combined uncertainty estimate for the broadband shortwave radiation fluxes at all five ARAD stations, using the methodology specified by the Guide to the Expression of Uncertainty in Measurement indicates that relative accuracies range from 1.5 to 2.9 % for large signals (global, direct: 1000 W m −2 , diffuse: 500 W m −2 ) and from 1.7 to 23 % (or 0.9 to 11.5 W m −2 ) for small signals (50 W m −2 ) (expanded uncertainties corresponding to the 95 % confidence level). If the directional response error of the pyranometers and the temperature response of the instruments and the data acquisition system (DAQ) are corrected, this expanded uncertainty reduces to 1.4 to 2.8 % for large signals and to 1.7 to 5.2 % (or 0.9-2.6 W m −2 ) for small signals. Thus, for large signals of global and diffuse radiation, BSRN target accuracies are met or nearly met (missed by less than 0.2 percentage points, pps) for 70 % of the ARAD measurements after this correction. For small signals of direct radiation, BSRN targets are achieved at two sites and nearly met (also missed by less than 0.2 pps) at the other sites. For small signals of global and diffuse radiation, targets are achieved at all stations. Additional accuracy gains can be achieved in the future through additional measurements, corrections and a further upgrade of the DAQ. However, to improve the accuracy of measurements of direct solar radiation, improved instrument accuracy is needed. ARAD could serve as a useful example for establishing state-of-the-art radiation monitoring at the national level with a multiple-purpose approach. Instrumentation, guidelines and tools (such as the data quality control) developed within ARAD are intended to increase monitoring capabilities of global radiation and thus designed to allow straightforward adoption in other regions, without high development costs.

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The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region

Cited by 265 publications

References 33 publications

On the forecast skill of a convection-permitting ensemble

On the forecast skill of a convection-permitting ensemble

Can riparian vegetation shade mitigate the expected rise in stream temperatures due to climate change during heat waves in a human-impacted pre-alpine river?

The Austrian radiation monitoring network ARAD – best practice and added value

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