The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

Devasthale, Abhay; Norin, Lars

doi:10.5194/amt-7-1605-2014

Cited by 9 publications

(6 citation statements)

References 30 publications

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“…This study covers data for the period between 2001 to 2015 for both precipitation data and damage data. In Sweden, extreme rainfall is mainly expected during the summer months June, July and August (Devasthale & Norin, ) and the majority of flood insurance damages occurs during these month (Figure ), both in Gothenburg and Malmö and also on a national scale.…”

Section: Methods and Datamentioning

confidence: 99%

The impact of intense rainfall on insurance losses in two Swedish cities

Blumenthal

Nyberg

2018

J Flood Risk Management

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While a major part of previous research in the field of flood damage has focused on water depth as the most important causal factor, little attention has been paid to the role of rainfall intensity. As a test, this paper used correlation and regression analyses to investigate rainfall intensity as a factor affecting flood damage. For a time period of 15 years, the relationship between insurance losses caused by floods and rainfall intensity data from rain gauges was examined in two Swedish cities. Another objective was to find an approach for damage functions based on rainfall intensity as explanatory variable. Using linear regression, two approaches with considerable high degrees of explanation were found–one based on an exponential function and one on a power function. Using a lower limit for rainfall intensity, the approaches reached degrees of explanation between 30 and 78%. From this study it was concluded that rainfall intensity during the summer months and the occurrence of insurance damages per day caused by floods were correlated and further that rainfall intensity has a great potential to explain urban flood damages. In the future, additional studies are needed to validate the proposed methods and integrate other flood damage affecting factors in the approach.

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Section: Methods and Datamentioning

confidence: 99%

The impact of intense rainfall on insurance losses in two Swedish cities

Blumenthal

Nyberg

2018

J Flood Risk Management

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“…Humidity profiles from the Atmospheric Infrared Sounder (AIRS) instrument flying on board NASA's Aqua satellite since 2002 are further used to investigate differences in the moisture advection during weather states (Chahine et al, 2006;Susskind et al, 2014;Devasthale et al, 2016). Aqua is part of the A-Train constellation of satellites and travels in front of CloudSat in the same orbit.…”

Section: Humidity Data From the Atmospheric Infrared Soundermentioning

confidence: 99%

The sensitivity of snowfall to weather states over Sweden

Norin¹,

Devasthale²,

L’Ecuyer³

2017

Atmos. Meas. Tech.

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Abstract. For a high-latitude country like Sweden snowfall is an important contributor to the regional water cycle. Furthermore, snowfall impacts surface properties, affects atmospheric thermodynamics, has implications for traffic and logistics management, disaster preparedness, and also impacts climate through changes in surface albedo and turbulent heat fluxes. For Sweden it has been shown that large-scale atmospheric circulation patterns, or weather states, are important for precipitation variability. Although the link between atmospheric circulation patterns and precipitation has been investigated for rainfall there are no studies focused on the sensitivity of snowfall to weather states over Sweden.In this work we investigate the response of snowfall to eight selected weather states. These weather states consist of four dominant wind directions together with cyclonic and anticyclonic circulation patterns and enhanced positive and negative phases of the North Atlantic Oscillation. The presented analysis is based on multiple data sources, such as ground-based radar measurements, satellite observations, spatially interpolated in situ observations, and reanalysis data. The data from these sources converge to underline the sensitivity of falling snow over Sweden to the different weather states.In this paper we examine both average snowfall intensities and snowfall accumulations associated with the different weather states. It is shown that, even though the heaviest snowfall intensities occur during conditions with winds from the south-west, the largest contribution to snowfall accumulation arrives with winds from the south-east. Large differences in snowfall due to variations in the North Atlantic Oscillation are shown as well as a strong effect of cyclonic and anticyclonic circulation patterns. Satellite observations are used to reveal the vertical structures of snowfall during the different weather states.

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“…The main focus of the present study is to quantitatively intercompare snowfall estimates from CloudSat and the ground-based weather radar network over Sweden. The Swedish radar network has been operational since the 1980s, and more than a decade of archived precipitation data exist to intercompare with space-based estimates (Michelson et al, 2000;Michelson and Koistinen, 2002;Michelson, 2006;Devasthale and Norin, 2014). Apart from offering an independent source of snowfall estimates, the high-latitude geographical position of the Swedish radars entails sampling of different meteorological regimes under which CloudSat CPR data could be intercompared.…”

Section: Norin Et Al: Intercomparison Of Snowfallmentioning

confidence: 99%

Intercomparison of snowfall estimates derived from the CloudSat Cloud Profiling Radar and the ground-based weather radar network over Sweden

et al. 2015

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Abstract. Accurate snowfall estimates are important for both weather and climate applications. Ground-based weather radars and space-based satellite sensors are often used as viable alternatives to rain gauges to estimate precipitation in this context. In particular, the Cloud Profiling Radar (CPR) on board CloudSat is proving to be a useful tool to map snowfall globally, in part due to its high sensitivity to light precipitation and its ability to provide near-global vertical structure. CloudSat snowfall estimates play a particularly important role in the high-latitude regions as other ground-based observations become sparse and passive satellite sensors suffer from inherent limitations. In this paper, snowfall estimates from two observing systems – Swerad, the Swedish national weather radar network, and CloudSat – are compared. Swerad offers a well-calibrated data set of precipitation rates with high spatial and temporal resolution, at very high latitudes. The measurements are anchored to rain gauges and provide valuable insights into the usefulness of CloudSat CPR's snowfall estimates in the polar regions. In total, 7.2 × 105 matchups of CloudSat and Swerad observations from 2008 through 2010 were intercompared, covering all but the summer months (June to September). The intercomparison shows encouraging agreement between the two observing systems despite their different sensitivities and user applications. The best agreement is observed when CloudSat passes close to a Swerad station (46–82 km), where the observational conditions for both systems are comparable. Larger disagreements outside this range suggest that both platforms have difficulty with shallow snow but for different reasons. The correlation between Swerad and CloudSat degrades with increasing distance from the nearest Swerad station, as Swerad's sensitivity decreases as a function of distance. Swerad also tends to overshoot low-level precipitating systems further away from the station, leading to an underestimation of snowfall rate and occasionally to missing precipitation altogether. Several statistical metrics – including the probability of detection, false alarm rate, hit rate, and Pierce's skill score – are calculated. The sensitivity of these metrics to the snowfall rate, as well as to the distance from the nearest radar station, are summarised. This highlights the strengths and the limitations of both observing systems at the lower and upper ends of the snowfall distributions as well as the range of uncertainties that can be expected from these systems in high-latitude regions.

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The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

Cited by 9 publications

References 30 publications

The impact of intense rainfall on insurance losses in two Swedish cities

The impact of intense rainfall on insurance losses in two Swedish cities

The sensitivity of snowfall to weather states over Sweden

Intercomparison of snowfall estimates derived from the CloudSat Cloud Profiling Radar and the ground-based weather radar network over Sweden

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