Intensity-dependent parameterization of elevation effects in precipitation analysis

Haiden, Thomas; Pistotnik, Georg

doi:10.5194/adgeo-20-33-2009

Cited by 50 publications

(40 citation statements)

References 12 publications

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“…Amending the rain gauge-radar combination, the scheme includes elevation effects on precipitation using an intensitydependent parameterization (Haiden and Pistotnik, 2009). A NWP model first guess is not required in the precipitation analysis; thus, such analyses are ideally suited as an independent reference to validate NWP models.…”

Section: Verification Datamentioning

confidence: 99%

See 1 more Smart Citation

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%

“…1), the Brier score (BS), components derived from its decomposition, reliability, resolution, and uncertainty (Brier, 1950;Murphy, 1973;respectively, Eqs. 2-5), and the continuous ranked probability score (CRPS, Hersbach 2000;Gneiting and Raftery, 2007;Eq. 6).…”

Section: T Schellander-gorgas Et Al: On the Forecast Skill Of A Conmentioning

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

“…On the other hand, lower radar data quality due to topographic shielding gives higher weight to the interpolated station data. Additionally, elevation effects are parameterized accounting for the increase of precipitation amounts with height (Haiden and Pistotnik, 2009). Figure 3 illustrates the combination algorithm in the case of 13 September 2014, 02:40 UTC.…”

Section: The Rapid-inca Precipitation Analysismentioning

confidence: 99%

Evaluation of high-resolution precipitation analyses using a dense station network

Kann

Meirold-Mautner

Schmid

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. The ability of radar-rain gauge merging algorithms to precisely analyse convective precipitation patterns is of high interest for many applications, e.g. hydrological modelling, thunderstorm warnings, and, as a reference, to spatially validate numerical weather prediction models. However, due to drawbacks of methods like crossvalidation and due to the limited availability of reference data sets on high temporal and spatial scales, an adequate validation is usually hardly possible, especially on an operational basis. The present study evaluates the skill of very high-resolution and frequently updated precipitation analyses (rapid-INCA) by means of a very dense weather station network (WegenerNet), operated in a limited domain of the southeastern parts of Austria (Styria). Based on case studies and a longer-term validation over the convective season 2011, a general underestimation of the rapid-INCA precipitation amounts is shown by both continuous and categorical verification measures, although the temporal and spatial variability of the errors is -by convective nature -high. The contribution of the rain gauge measurements to the analysis skill is crucial. However, the capability of the analyses to precisely assess the convective precipitation distribution predominantly depends on the representativeness of the stations under the prevalent convective condition.

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“…Systematic model errors can arise during the regionalisation of rainfall in alpine areas, when e.g. the elevation dependency is not considered (Haiden and Pistotnik, 2009). Quantitative areal rainfall estimates from radar products are, although they contain precious information on the rainfall structure, still afflicted with significant uncertainties (Krajewski et al, 2010;Krajewski and Smith, 2002).…”

Section: Uncertainties In Catchment Precipitationmentioning

confidence: 99%

From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

Herrnegger

Nachtnebel

Schulz

2015

Hydrol. Earth Syst. Sci.

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Abstract. Rainfall exhibits a large spatio-temporal variability, especially in complex alpine terrain. Additionally, the density of the monitoring network in mountainous regions is low and measurements are subjected to major errors, which lead to significant uncertainties in areal rainfall estimates. In contrast, the most reliable hydrological information available refers to runoff, which in the presented work is used as input for an inverted HBV-type rainfall-runoff model that is embedded in a root finding algorithm. For every time step a rainfall value is determined, which results in a simulated runoff value closely matching the observed runoff. The inverse model is applied and tested to the Schliefau and Krems catchments, situated in the northern Austrian Alpine foothills. The correlations between inferred rainfall and station observations in the proximity of the catchments are of similar magnitude compared to the correlations between station observations and independent INCA (Integrated Nowcasting through Comprehensive Analysis) rainfall analyses provided by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG). The cumulative precipitation sums also show similar dynamics. The application of the inverse model is a promising approach to obtain additional information on mean areal rainfall. This additional information is not solely limited to the simulated hourly data but also includes the aggregated daily rainfall rates, which show a significantly higher correlation to the observed values. Potential applications of the inverse model include gaining additional information on catchment rainfall for interpolation purposes, flood forecasting or the estimation of snowmelt contribution. The application is limited to (smaller) catchments, which can be represented with a lumped model setup, and to the estimation of liquid rainfall.

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Intensity-dependent parameterization of elevation effects in precipitation analysis

Cited by 50 publications

References 12 publications

On the forecast skill of a convection-permitting ensemble

On the forecast skill of a convection-permitting ensemble

Evaluation of high-resolution precipitation analyses using a dense station network

From runoff to rainfall: inverse rainfall–runoff modelling in a high temporal resolution

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