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Publikasjoner (10 av 16) Visa alla publikasjoner
Lindskog, M. & Landelius, T. (2018). Prognoser av Solstrålning. Polarfront (168), 41-44
Åpne denne publikasjonen i ny fane eller vindu >>Prognoser av Solstrålning
2018 (svensk)Inngår i: Polarfront, nr 168, s. 41-44Artikkel i tidsskrift (Annet vitenskapelig) Published
sted, utgiver, år, opplag, sider
Svenska Meteorologiska Sällskapet, 2018
HSV kategori
Forskningsprogram
Meteorologi; Fjärranalys
Identifikatorer
urn:nbn:se:smhi:diva-5156 (URN)
Tilgjengelig fra: 2019-02-01 Laget: 2019-02-01 Sist oppdatert: 2019-02-01bibliografisk kontrollert
Gustafsson, N., Janjić, T., Schraff, C., Leuenberger, D., Weissmann, M., Reich, H., . . . Fujita, T. (2018). Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres. Quarterly Journal of thte Royal Meteorology Society, 144(711)
Åpne denne publikasjonen i ny fane eller vindu >>Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres
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2018 (engelsk)Inngår i: Quarterly Journal of thte Royal Meteorology Society, ISSN 1350-4827, Vol. 144, nr 711Artikkel i tidsskrift (Annet vitenskapelig) Published
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-4938 (URN)10.1002/qj.3179 (DOI)
Tilgjengelig fra: 2018-08-21 Laget: 2018-08-21 Sist oppdatert: 2018-08-21bibliografisk kontrollert
Lindskog, M., Ridal, M., Thorsteinsson, S. & Ning, T. (2017). Data assimilation of GNSS zenith total delays from a Nordic processing centre. Atmospheric Chemistry And Physics, 17(22), 13983-13998
Åpne denne publikasjonen i ny fane eller vindu >>Data assimilation of GNSS zenith total delays from a Nordic processing centre
2017 (engelsk)Inngår i: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 17, nr 22, s. 13983-13998Artikkel i tidsskrift (Fagfellevurdert) Published
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-4450 (URN)10.5194/acp-17-13983-2017 (DOI)000416151800001 ()
Tilgjengelig fra: 2017-12-12 Laget: 2017-12-12 Sist oppdatert: 2017-12-12bibliografisk kontrollert
Sanchez Arriola, J., Lindskog, M., Thorsteinsson, S. & Bojarova, J. (2016). Variational Bias Correction of GNSS ZTD in the HARMONIE Modeling System. Journal of Applied Meteorology and Climatology, 55(5), Article ID UNSP 1259.
Åpne denne publikasjonen i ny fane eller vindu >>Variational Bias Correction of GNSS ZTD in the HARMONIE Modeling System
2016 (engelsk)Inngår i: Journal of Applied Meteorology and Climatology, ISSN 1558-8424, E-ISSN 1558-8432, Vol. 55, nr 5, artikkel-id UNSP 1259Artikkel i tidsskrift (Fagfellevurdert) Published
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-2157 (URN)10.1175/JAMC-D-15-0137.1 (DOI)000376241200001 ()
Tilgjengelig fra: 2016-06-15 Laget: 2016-06-15 Sist oppdatert: 2017-11-28bibliografisk kontrollert
Stengel, M., Lindskog, M., Unden, P. & Gustafsson, N. (2013). The impact of cloud-affected IR radiances on forecast accuracy of a limited-area NWP model. Quarterly Journal of the Royal Meteorological Society, 139(677), 2081-2096
Åpne denne publikasjonen i ny fane eller vindu >>The impact of cloud-affected IR radiances on forecast accuracy of a limited-area NWP model
2013 (engelsk)Inngår i: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 139, nr 677, s. 2081-2096Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The impact of cloud-affected satellite radiances on numerical weather prediction (NWP) accuracy is investigated. The NWP model used is the HIgh Resolution Limited Area Model (HIRLAM). Its four-dimensional variational data assimilation (4D-Var) system was used to assimilate cloud-affected infrared (IR) radiances from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). Cloud parameters are modelled internally in the observation operator and used in the radiative transfer calculations. The interaction between the cloud parameters and the model control vector variables is incorporated in the adjoint version of the observation operator, which is used to derive cloud-affected Jacobians prior to the inner-loop minimization of the cost function. The developed framework supports an extensive usage of satellite observations with spatial coverage extended into cloudy regions, which therefore provides additional analysis increments and supports a more accurate description of the atmospheric state. In extended assimilation and forecast experiments the total number of assimilated satellite observations could be increased by approximately 10%. This was associated with a clear indication of a positive impact of cloud-affected radiances on the moisture and geopotential height fields of the NWP model analysis and forecast accuracy when used on top of clear-sky radiance observations. This is revealed by reduced analysis errors of the total integrated water vapour and by reduced forecast errors in the mid and upper troposphere.

Emneord
assimilation, cloudy radiances, numerical weather prediction, limited-area NWP model
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-344 (URN)10.1002/qj.2102 (DOI)000328348000010 ()
Tilgjengelig fra: 2015-04-14 Laget: 2015-03-31 Sist oppdatert: 2017-12-04bibliografisk kontrollert
Gustafsson, N., Huang, X.-Y., Yang, X., Mogensen, K., Lindskog, M., Vignes, O., . . . Thorsteinsson, S. (2012). Four-dimensional variational data assimilation for a limited area model. Tellus. Series A, Dynamic meteorology and oceanography, 64, Article ID 14985.
Åpne denne publikasjonen i ny fane eller vindu >>Four-dimensional variational data assimilation for a limited area model
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2012 (engelsk)Inngår i: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 64, artikkel-id 14985Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A 4-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system is described in this article. The innovative approaches to the multi-incremental formulation, the weak digital filter constraint and the semi-Lagrangian time integration are highlighted with some details. The implicit dynamical structure functions are discussed using single observation experiments, and the sensitivity to various parameters of the 4D-Var formulation is illustrated. To assess the meteorological impact of HIRLAM 4D-Var, data assimilation experiments for five periods of 1 month each were performed, using HIRLAM 3D-Var as a reference. It is shown that the HIRLAM 4D-Var consistently out-performs the HIRLAM 3D-Var, in particular for cases with strong mesoscale storm developments. The computational performance of the HIRLAM 4D-Var is also discussed.

Emneord
data assimilation, analysis, numerical weather prediction
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-490 (URN)10.3402/tellusa.v64i0.14985 (DOI)000300396800003 ()
Tilgjengelig fra: 2015-04-14 Laget: 2015-04-14 Sist oppdatert: 2017-12-04bibliografisk kontrollert
Ridal, M., Lindskog, M., Gustafsson, N. & Haase, G. (2011). Optimized advection of radar reflectivities. Atmospheric research, 100(2-3), 213-225
Åpne denne publikasjonen i ny fane eller vindu >>Optimized advection of radar reflectivities
2011 (engelsk)Inngår i: Atmospheric research, ISSN 0169-8095, E-ISSN 1873-2895, Vol. 100, nr 2-3, s. 213-225Artikkel i tidsskrift (Fagfellevurdert) Published
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.

Emneord
Nowcasting, Radar, Advection, Variational data assimilation
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-521 (URN)10.1016/j.atmosres.2010.12.016 (DOI)000290501600007 ()
Tilgjengelig fra: 2015-04-17 Laget: 2015-04-15 Sist oppdatert: 2017-12-04bibliografisk kontrollert
Stengel, M., Lindskog, M., Unden, P., Gustafsson, N. & Bennartz, R. (2010). An extended observation operator in HIRLAM 4D-VAR for the assimilation of cloud-affected satellite radiances. Quarterly Journal of the Royal Meteorological Society, 136(649), 1064-1074
Åpne denne publikasjonen i ny fane eller vindu >>An extended observation operator in HIRLAM 4D-VAR for the assimilation of cloud-affected satellite radiances
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2010 (engelsk)Inngår i: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 136, nr 649, s. 1064-1074Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

An extended observation operator for the direct assimilation of cloud-affected infrared satellite radiances in the High Resolution Limited Area Model (HIRLAM) is examined. The operator includes a simplified moist-physics scheme, which enables the diagnosis of cloudiness in itself using background values of temperature, moisture and surface pressure. Subsequently, a radiative transfer model provides simulated cloud-affected radiances to be used as background equivalents to the satellite observations. The observation operator was evaluated by using infrared observations measured by the Spinning Enhanced Visible and Infrared Imager (SEVIRI). An observation-screening procedure, which incorporates SEVIRI cloud-retrieval products, supports an improved selection of usable cloudy scenes, leading to good agreement between the observations and background equivalents. The tangent-linear observation operator was verified against finite differences from its nonlinear formulation. The increments revealed a near-linear behaviour for the selected channels for a large number of cases. The adjoint observation operator was used to derive brightness-temperature sensitivities with respect to temperature and moisture changes in the presence of radiance-affecting clouds. Differences from the clear-sky sensitivities were found in and below clouds. In a four-dimensional variational data assimilation experiment, cloud-affected SEVIRI observations were assimilated, resulting in additional increments in both moisture and wind fields. The corresponding analysis fields revealed a reduced deviation from the observations for the majority of all cloudy scenes and a reduced bias for wind and temperature in the upper troposphere against independent radiosonde observations. Overall, our results highlight the capability of this observation operator in the HIRLAM assimilation system and encourage its application for the extended usage of cloudy satellite observations in numerical weather prediction. Copyright (C) 2010 Royal Meteorological Society

Emneord
limited-area NWP model, cloudy radiances, cloud scheme
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-570 (URN)10.1002/qj.621 (DOI)000279407000017 ()
Tilgjengelig fra: 2015-04-22 Laget: 2015-04-20 Sist oppdatert: 2017-12-04bibliografisk kontrollert
Lindskog, M., Dee, D., Tremolet, Y., Andersson, E., Radnoti, G. & Fisher, M. (2009). A weak-constraint four-dimensional variational analysis system in the stratosphere. Quarterly Journal of the Royal Meteorological Society, 135(640), 695-706
Åpne denne publikasjonen i ny fane eller vindu >>A weak-constraint four-dimensional variational analysis system in the stratosphere
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2009 (engelsk)Inngår i: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 135, nr 640, s. 695-706Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A weak-constraint four-dimensional variational (4D-Var) analysis system designed to correct stratospheric model errors has been evaluated. Verifications against upper-level radiosonde temperature observations and Stratospheric Sounding Unit (SSU) radiance data show that the addition of a weak constraint in the stratosphere call greatly reduce analysis bias. Both single-observation analysis experiments and extended assimilations have been performed to help us understand the impact of the model error covariance specifications required for the weak-constraint formulation. It is found that the use of multivariate balance constraints similar to those implemented in background-error covariances can be problematic. Copyright (C) 2009 Royal Meteorological Society

Emneord
variational data assimilation, weak-constraint 4D-Var, stratospheric model error
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-622 (URN)10.1002/qj.392 (DOI)000266552400010 ()
Tilgjengelig fra: 2015-04-23 Laget: 2015-04-21 Sist oppdatert: 2017-12-04bibliografisk kontrollert
Stengel, M., Undén, P., Lindskog, M., Dahlgren, P., Gustafsson, N. & Bennartz, R. (2009). Assimilation of SEVIRI infrared radiances with HIRLAM 4D-Var. Quarterly Journal of the Royal Meteorological Society, 135(645), 2100-2109
Åpne denne publikasjonen i ny fane eller vindu >>Assimilation of SEVIRI infrared radiances with HIRLAM 4D-Var
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2009 (engelsk)Inngår i: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 135, nr 645, s. 2100-2109Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Four-dimensional variational data assimilation (4D-Var) systems are ideally suited to obtain the best possible initial model state by utilizing information about the dynamical evolution of the. atmospheric state from observations, such as satellite measurements, distributed over a certain period of time. In recent years, 4D-Var systems have been developed for several global and limited-area models. At the same time, spatially and temporally highly resolved satellite observations, as for example performed by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board the Meteosat Second Generation satellites, have become available. Here we demonstrate the benefit of a regional NWP model's analyses and forecasts gained by the assimilation of those radiances. The 4D-Var system of the High Resolution Limited Area Model (HIRLAM) has been adjusted to utilize three of SEVIRI's infrared channels (located around 6.2 mu m, 7.3 mu m, and 13.4 mu m, respectively) under clear-sky and low-level cloud conditions. Extended assimilation and forecast experiments show that the main direct impact of assimilated SEVIRI radiances on the atmospheric analysis were additional tropospheric humidity and wind increments. Forecast verification reveals a positive impact for almost all upper-air variables throughout the troposphere. Largest improvements are found for humidity and geopotential height in the middle troposphere. The observations in regions of low-level clouds provide especially beneficial information to the NWP system, which highlights the importance of satellite observations in cloudy areas for further improvements in the accuracy of weather forecasts. Copyright (C) 2009 Royal Meteorological Society

Emneord
limited-area NWP model, IR satellite observations, clear-sky conditions, low-level clouds
HSV kategori
Forskningsprogram
Meteorologi
Identifikatorer
urn:nbn:se:smhi:diva-605 (URN)10.1002/qj.501 (DOI)000273575200013 ()
Tilgjengelig fra: 2015-04-27 Laget: 2015-04-21 Sist oppdatert: 2017-12-04bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0003-4870-5459
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