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  • 1.
    Arheimer, Berit
    et al.
    SMHI, Research Department, Hydrology.
    Lindström, Göran
    SMHI, Research Department, Hydrology.
    Olsson, Jonas
    SMHI, Research Department, Hydrology.
    A systematic review of sensitivities in the Swedish flood-forecasting system2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 275-284Article, review/survey (Refereed)
    Abstract [en]

    Since the early 1970s operational flood forecasts in Sweden have been based on the hydrological HBV model. However, the model is only one component in a chain of processes for production of hydrological forecasts. During the last 35 years there has been considerable work on improving different parts of the forecast procedure and results from specific studies have been reported frequently. Yet, the results have not been compared in any overall assessment of potential for improvements. Therefore we formulated and applied a method for translating results from different studies to a common criterion of error reduction. The aim was to quantify potential improvements in a systems perspective and to identify in which part of the production chain efforts would result in significantly better forecasts. The most sensitive (> 20% error reduction) components were identified for three different operational-forecast types. From the analyses of historical efforts to minimise the errors in the Swedish flood-forecasting system, it was concluded that 1) general runoff simulations and predictions could be significantly improved by model structure and calibration, model equations (e.g. evapotranspiration expression), and new precipitation input using radar data as a complement to station gauges; 2) annual spring-flood forecasts could be significantly improved by better seasonal meteorological forecast, fresh re-calibration of the hydrological model based on long time-series, and data assimilation of snow-pack measurements using georadar or gamma-ray technique; 3) short-term (2 days) forecasts could be significantly improved by up-dating using an auto-regressive method for discharge, and by ensembles of meteorological forecasts using the median at occasions when the deterministic forecast is out of the ensemble range. The study emphasises the importance of continuously evaluating the entire production chain to search for potential improvements of hydrological forecasts in the operational environment. (C) 2010 Elsevier B.V. All rights reserved.

  • 2. Nishiyama, Koji
    et al.
    Endo, Shinichi
    Jinno, Kenji
    Uvo, Cintia Bertacchi
    Olsson, Jonas
    SMHI, Research Department, Hydrology.
    Berndtsson, Ronny
    Identification of typical synoptic patterns causing heavy rainfall in the rainy season in Japan by a Self-Organizing Map2007In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 83, no 2-4, p. 185-200Article in journal (Refereed)
    Abstract [en]

    In order to systematically and visually understand well-known but qualitative and complex relationships between synoptic fields and heavy rainfall events in Kyushu Islands, southwestern Japan, during the BAIU season, these synoptic fields were classified using the Self-Organizing Map (SOM), which can convert complex non-linear features into simple two-dimensional relationships. It was assumed that the synoptic field patterns could be simply expressed by the spatial distribution of (1) wind components at the 850 hPa level and (2) precipitable water (PW) defined by the water vapor amount contained in a vertical column of the atmosphere. By the SOM algorithm and the clustering techniques of the U-matrix and the K-means, the synoptic fields could be divided into eight kinds of patterns (clusters). One of the clusters has the notable spatial features represented by a large PW content accompanied by strong wind components known as low-level jet (LLJ). The features of this cluster indicate a typical synoptic field pattern that frequently causes heavy rainfall in Kyushu during the rainy season. In addition, an independent data set was used for validating the performance of the trained SOM. The results indicated that the SOM could successfully extract heavy rainfall events related to typical synoptic field patterns of the BAIU season. Interestingly, one specific SOM unit was closely related to the occurrence of disastrous heavy rainfall events observed during both training and validation periods. From these results, the trained SOM showed good performance for identifying synoptic fields causing heavy rainfall also in the validation period. We conclude that the SOM technique may be an effective tool for classifying complicated non-linear synoptic fields and identifying heavy rainfall events to some degree. (c) 2006 Elsevier B.V. All rights reserved.

  • 3.
    Olsson, Jonas
    et al.
    SMHI, Research Department, Hydrology.
    Berggren, K.
    Olofsson, M.
    Viklander, M.
    Applying climate model precipitation scenarios for urban hydrological assessment: A case study in Kalmar City, Sweden2009In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 92, no 3, p. 364-375Article in journal (Refereed)
    Abstract [en]

    There is growing interest in the impact of climate change on urban hydrological processes. Such assessment may be based on the precipitation output from climate models. To date, the model resolution in both time and space has been too low for proper assessment, but at least in time the resolution of available model output is approaching urban scales. In this paper, 30-min precipitation from a model grid box covering Kalmar City, Sweden, is compared with high-resolution (tipping-bucket) observations from a gauge in Kalmar. The model is found to overestimate the frequency of low rainfall intensities, and therefore the total volume, but reasonably well reproduce the highest intensities. Adapting climate model data to urban drainage applications can be done in several ways but a popular way is the so-called Delta Change (DC) method. In this method, relative changes in rainfall characteristics estimated from climate model output are transferred to an observed rainfall time series, generally by multiplicative factors. In this paper, a version of the method is proposed in which these DC factors (DCFs) are related to the rainfall intensity level. This is achieved by calculating changes in the probability distribution of rainfall intensities and modelling the DCFs as a function of percentile. Applying this method in Kalmar indicated that in summer and autumn, high intensities will increase by 20-60% by year 2100, whereas low intensities remain stable or decrease. In winter and spring, generally all intensity levels increase similarly. The results were transferred to the observed time series by varying the volume of the tipping bucket to reflect the estimated intensity changes on a 30-min time scale. In an evaluation of the transformed data at a higher 5-min resolution, effects on the intensity distribution as well as single precipitation events were demonstrated. In particular, qualitatively different changes in peak intensity and total volume are attainable, which is required in light of expected future changes of the precipitation process and a step forward as compared with simpler DC approaches. Using the DC transformed data as input in urban drainage simulations for a catchment in Kalmar indicated an increase of the number of surface floods by 20-45% during this century. (C) 2009 Elsevier B.V. All rights reserved.

  • 4.
    Ridal, Martin
    et al.
    SMHI, Research Department, Meteorology.
    Lindskog, Magnus
    SMHI, Research Department, Meteorology.
    Gustafsson, Nils
    SMHI, Research Department, Meteorology.
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Optimized advection of radar reflectivities2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 213-225Article in journal (Refereed)
    Abstract [en]

    A nowcasting system for generation of short-range precipitation forecasts has been developed at the Swedish Meteorological and Hydrological Institute (SMHI). The methodology consists of utilising a time-series of radar reflectivity composites for deriving an advection field, which will give a better representation of the motion of the precipitation pattern compared to a model wind field. The advection field is derived applying a 4-dimensional variational data assimilation technique. The resulting field is then used for a semi-Lagrangian advection of the latest available reflectivity field forward in time. During the forecast, the advected field is gradually replaced by a numerical weather prediction forecast in order to include the onset of convection and advection into the radar coverage area. In an idealised example with simulated observations the functionality of the method is demonstrated. For a case study of a full scale example the resulting precipitation forecast shows large improvements compared to the operational numerical weather prediction model used at SMHI, especially for forecasts up to three hours, where the largest influence from the radar advection occurs. In an objective validation of the structure, amplitude and location of modelled precipitation, where the forecasts are compared to radar observations, these findings are confirmed. The same validation of model runs over a longer time period also clearly indicates that the amplitude, structure and location of the precipitation patterns are significantly improved as compared to a short-range forecast from the operational forecast model used at SMHI. (C) 2010 Elsevier B.V. All rights reserved.

  • 5. Rossa, Andrea
    et al.
    Liechti, Katharina
    Zappa, Massimiliano
    Bruen, Michael
    Germann, Urs
    Haase, Günther
    SMHI, Research Department, Atmospheric remote sensing.
    Keil, Christian
    Krahe, Peter
    The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 150-167Article, review/survey (Refereed)
    Abstract [en]

    Quantifying uncertainty in flood forecasting is a difficult task, given the multiple and strongly nonlinear model components involved in such a system. Much effort has been and is being invested in the quest of dealing with uncertain precipitation observations and forecasts and the propagation of such uncertainties through hydrological and hydraulic models predicting river discharges and risk for inundation. The COST 731 Action is one of these and constitutes a European initiative which deals with the quantification of forecast uncertainty in hydro-meteorological forecast systems. COST 731 addresses three major lines of development: (1) combining meteorological and hydrological models to form a forecast chain, (2) propagating uncertainty information through this chain and make it available to end users in a suitable form, (3) advancing high-resolution numerical weather prediction precipitation forecasts by using non-conventional observations from, for instance, radar to determine details in the initial conditions on scales smaller than what can be resolved by conventional observing systems. Recognizing the interdisciplinarity of the challenge COST 731 has organized its work forming Working Groups at the interfaces between the different scientific disciplines involved, i.e. between observation and atmospheric (and hydrological) modelling (WG-1), between atmospheric and hydrologic modelling (WG-2) and between hydrologic modelling and end-users (WG-3). This paper summarizes the COST 731 activities and its context, provides a review of the recent progress made in dealing with uncertainties in flood forecasting, and sets the scene for the papers of this Thematic Issue. In particular, a bibliometric analysis highlights the strong recent increase in addressing the uncertainty analysis in flood forecasting from an integrated perspective. Such a perspective necessarily involves the area of meteorology, hydrology, and decision making in order to take operational advantage of the scientific progress, an aspect in which COST 731 is successfully contributing to furthering the flood damage mitigation capabilities in Europe. (C) 2010 Elsevier B.V. All rights reserved.

  • 6. Salonen, Kirsti
    et al.
    Haase, Gunther
    SMHI, Research Department, Atmospheric remote sensing.
    Eresmaa, Reima
    Hohti, Harri
    Jarvinen, Heikki
    Towards the operational use of Doppler radar radial winds in HIRLAM2011In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, no 2-3, p. 190-200Article in journal (Refereed)
    Abstract [en]

    This article discusses the pre-operational development for data assimilation of radial wind observations in the High Resolution Limited Area Model (HIRLAM) at the Finnish Meteorological Institute (FMI). The HIRLAM variational data assimilation system includes all the needed tools for exploitation of radial wind observations. A measurement task designed especially for the radial wind data assimilation purposes has been implemented to the FMI radar network. Observation quality monitoring indicates that the main error sources for the radial wind observations are ground clutter and velocity ambiguity. The HIRLAM quality control procedures are able to detect and reject most of these erroneous observations. Impact studies show encouraging results. Surface verification indicates that the use of radar wind observations has a positive impact on 10 m wind forecasts. Precipitation forecasts are also slightly improved. Upper air verification shows positive impact on wind and temperature forecasts at the 925-700 hPa levels. (C) 2010 Elsevier B.V. All rights reserved.

  • 7. Schroeder, Marc
    et al.
    van Lipzig, Nicole P. M.
    Ament, Felix
    Chaboureau, Jean-Pierre
    Crewell, Susanne
    Fischer, Juergen
    Matthias, Volker
    van Meijgaard, Erik
    Walther, Andi
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Model predicted low-level cloud parameters Part II: Comparison with satellite remote sensing observations during the BALTEX Bridge Campaigns2006In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 82, no 1-2, p. 83-101Article in journal (Refereed)
    Abstract [en]

    A pressing task in numerical weather prediction and climate modelling is the evaluation of modelled cloud fields. Recent progress in spatial and temporal resolution of satellite remote sensing increases the potential of such evaluation efforts. This paper presents new methodologies to compare satellite remote sensing observations of clouds and output of atmospheric models and demonstrates their usefulness for evaluation. The comparison is carried out for two MODerate resolution Imaging Spectrometer (MODIS) scenes from the BALTEX Bridge Campaigns. Both scenes are characterised by low-level clouds with a substantial amount of liquid water. Cloud cover and cloud optical thickness of five different models, LM, Wso-NH, MM5 (non-hydrostatic models), RACMO2, and RCA (regional climate models) as well as corresponding retrievals from high resolution remote sensing observations of MODIS onboard the Terra satellite form the basis of a statistical analysis to compare the data sets. With the newly introduced patchiness parameters it is possible to separate differences between the two scenes on the one hand and between the models and the satellite on the other hand. We further introduce a new approach to spatially aggregate cloud optical thickness. Generally the models overestimate cloud optical thickness which can in part be ascribed to the lack of subgrid-scale variability. However, UM underestimates the frequency of occurrence of cloud optical thickness at values around 25. Furthermore, we compare the standard operational output of the non-hydrostatic models to simulations of the same models including parameterised shallow convection. However, clear improvements in the representation of low-level clouds are not found for these models. A change of the coefficients for autoconversion in RCA shows that LWP and precipitation strongly depend on this parameter. Refined vertical resolution, implemented in RACMO2, leads to a better agreement between model and satellite but still leaves room for further improvements. In general, this study reveals deficiencies of the models in representing low-level clouds, in particular for a stratiform cloud. (c) 2006 Elsevier B.V. All rights reserved.

  • 8. van Lipzig, Nicole P. M.
    et al.
    Schroeder, Marc
    Crewell, Susanne
    Ament, Felix
    Chaboureau, Jean-Pierre
    Loehnert, Ulrich
    Matthias, Volker
    van Meijgaard, Erik
    Quante, Markus
    Willén, Ulrika
    SMHI, Research Department, Climate research - Rossby Centre.
    Yen, Wenchieh
    Model predicted low-level cloud parameters - Part I: Comparison with observations from the BALTEX Bridge Campaigns2006In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 82, no 1-2, p. 55-82Article in journal (Refereed)
    Abstract [en]

    The BALTEX Bridge Campaigns (BBC), which were held in the Netherlands in 2001 and 2003 around the Cabauw Experimental Site for Atmospheric Research (CESAR), have provided detailed information on clouds. This paper is an illustration of how these measurements can be used to investigate whether 'state-of-the-art' atmospheric models are capable of adequately representing clouds. Here, we focus on shallow low-level clouds with a substantial amount of liquid water. In situ, ground-based and satellite remote sensing measurements were compared with the output of three non-hydrostatic regional models (Lokal-Modell, LM.- M&so-NH: fifth-generation Mesoscale Model, MM5) and two hydrostatic regional climate models (Regional Atmospheric Climate Model version 2, RACMO2; Rossby Centre Atmospheric Model, RCA). For the two selected days, Meso-NH and MM5 reproduce the measured vertical extent of the shallow clouds, but the liquid water content of the clouds is generally overestimated. In LM and the climate models the inversion is too weak and located at a level too close to the surface resulting in an overestimation of the vertical extent of the clouds. A sensitivity integration with RACM02 shows that the correspondence between model output and measurements can be improved by a doubling of the vertical resolution; this induces an increase in the modelled inversion strenath and cloud top pressure. LM and Meso-NH underestimate the lifetime of clouds. A comparison between model output and cloud cover derived from the Moderate Resolution Imaging Spectrometer (MODIS) indicates that this deficiency is not due to advection of too small cloud systems,- it is rather due to an overestimation of the variability in the vertical velocity. All models overestimate the specific humidity near the surface and underestimate it at higher atmospheric levels, indicating that the models underestimate the mixing of moisture in the boundary layer. This deficiency is slightly reduced by inclusion of parameterised shallow convection in the non-hydrostatic models, which enhances the mixing of heat and moisture in the boundary layer. Consequently, the explicitly resolved updrafts weaken resulting in reduced condensation rates and lower liquid water path. The temporal variability of cloud occurrence is hardly affected by inclusion of parameterised shallow convection. (c) 2006 Elsevier B.V. All rights reserved.

  • 9. Walther, Alexander
    et al.
    Jeong, Jee-Hoon
    Nikulin, Grigory
    SMHI, Research Department, Climate research - Rossby Centre.
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Chen, Deliang
    Evaluation of the warm season diurnal cycle of precipitation over Sweden simulated by the Rossby Centre regional climate model RCA32013In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 119, p. 131-139Article in journal (Refereed)
    Abstract [en]

    This study examines the diurnal cycle of precipitation over Sweden for the warm season (April to September) both in hourly observational data and in simulations from the Rossby Centre regional climate model (RCA3). A series of parallel long-term simulations of RCA3 with different horizontal resolutions - 50, 25, 12, and 6 km - were analyzed to investigate the sensitivity of the model's horizontal resolution to the simulated diurnal cycle of precipitation. Overall, a clear distinction between an afternoon peak for inland stations and an early morning peak for stations along the Eastern coast is commonly found both in observation and model results. However, the diurnal cycle estimated from the model simulations show too early afternoon peaks with too large amplitude compared to the observation. Increasing horizontal model resolution tends to reduce this bias both in peak timing and amplitude, but this resolution effect seems not to be monotonic; this is clearly seen only when comparing coarser resolution results with the 6 km resolution result. As the resolution increases, the peak timing and amplitude of the diurnal cycle of resolved large-scale precipitation become more similar to the observed cycle of total precipitation while the contribution of subgrid scale convective precipitation to the total precipitation decreases. An increase in resolution also tends to reduce too much precipitation of relatively light intensity over inland compared to the observation, which may also contribute to the more realistic simulation of the afternoon peak in convective precipitation. (C) 2011 Elsevier B.V. All rights reserved.

  • 10. Willems, P.
    et al.
    Arnbjerg-Nielsen, K.
    Olsson, Jonas
    SMHI, Research Department, Hydrology.
    Nguyen, V. T. V.
    Climate change impact assessment on urban rainfall extremes and urban drainage: Methods and shortcomings2012In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 103, p. 106-118Article in journal (Refereed)
    Abstract [en]

    Cities are becoming increasingly vulnerable to flooding because of rapid urbanization, installation of complex infrastructure, and changes in the precipitation patterns caused by anthropogenic climate change. The present paper provides a critical review of the current state-of-the-art methods for assessing the impacts of climate change on precipitation at the urban catchment scale. Downscaling of results from global circulation models or regional climate models to urban catchment scales are needed because these models are not able to describe accurately the rainfall process at suitable high temporal and spatial resolution for urban drainage studies. The downscaled rainfall results are however highly uncertain, depending on the models and downscaling methods considered. This uncertainty becomes more challenging for rainfall extremes since the properties of these extremes do not automatically reflect those of average precipitation. In this paper, following an overview of some recent advances in the development of innovative methods for assessing the impacts of climate change on urban rainfall extremes as well as on urban hydrology and hydraulics, several existing difficulties and remaining challenges in dealing with this assessment are discussed and further research needs are described. (C) 2011 Elsevier B.V. All rights reserved.

  • 11.
    Willén, Ulrika
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Crewell, S
    Baltink, H K
    Sievers, O
    Assessing model predicted vertical cloud structure and cloud overlap with radar and lidar ceilometer observations for the Baltex Bridge Campaign of CLIWA-NET2005In: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 75, no 3, p. 227-255Article in journal (Refereed)
    Abstract [en]

    The cloud vertical distribution and overlap of four large-scale models operating at different horizontal and vertical resolutions have been assessed using radar and lidar observations from the Baltex Bridge Campaign of CLIWA-NET. The models range from the global European Centre for Medium range Weather Forecast (ECMWF) model, to the Regional Atmospheric Climate Model (RACMO) and the Rossby Centre Atmospheric (RCA) regional climate model, to the non-hydrostatic meso-scale Lokal Model (LM). Different time averaging periods for the radar data were used to estimate the uncertainty of the point-to-space transformations of the observations. Relative to the observations, all models underestimated the height of the lowest cloud base. Clouds occurred more frequently in the models but with smaller cloud fractions below 7 km. The findings confirm previous cloud radar studies which found that models overestimate cloud fractions above 7 km. Radar-observed clouds were often thinner than the model vertical resolutions, which can have serious implications on model cloud overlap and radiation fluxes. The radar-derived cloud overlap matrix, which takes into account the overlap of all vertical layers, was found to be close to maximum-random overlap. Using random overlap for vertically continuous clouds with vertical gradients in cloud fraction larger than 40-50% per kilometre gave the best fit to the data. The gradient approach could be improved by making it resolution- and cloud system-dependent. Previous cloud radar overlap studies have considered the overlap of two cloud layers as a function of maximum and random overlap. Here, it was found that the two-layer overlap could be modelled by a mixture of maximum and minimum overlap. (c) 2005 Elsevier B.V. All rights reserved.

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