Change search
Link to record
Permanent link

Direct link
BETA
Alternative names
Publications (10 of 33) Show all publications
Zaplotnik, Z., Zagar, N. & Gustafsson, N. (2018). An intermediate-complexity model for four-dimensional variational data assimilation including moist processes. Quarterly Journal of the Royal Meteorological Society, 144(715), 1772-1787
Open this publication in new window or tab >>An intermediate-complexity model for four-dimensional variational data assimilation including moist processes
2018 (English)In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 144, no 715, p. 1772-1787Article in journal (Refereed) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-5009 (URN)10.1002/qj.3338 (DOI)000448651000006 ()
Available from: 2018-11-23 Created: 2018-11-23 Last updated: 2018-11-23Bibliographically approved
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)
Open this publication in new window or tab >>Survey of data assimilation methods for convective‐scale numerical weather prediction at operational centres
Show others...
2018 (English)In: Quarterly Journal of thte Royal Meteorology Society, ISSN 1350-4827, Vol. 144, no 711Article in journal (Other academic) Published
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-4938 (URN)10.1002/qj.3179 (DOI)
Available from: 2018-08-21 Created: 2018-08-21 Last updated: 2018-08-21Bibliographically approved
Bengtsson,, L., Gustafsson, N., Döös, B., Söderman, D., Moen, L., Thompson, T., . . . Kållberg, P. (2016). The Meteorological Auto Code (MAC) and Numerical Weather Prediction (NWP) at SMHI.
Open this publication in new window or tab >>The Meteorological Auto Code (MAC) and Numerical Weather Prediction (NWP) at SMHI
Show others...
2016 (English)Report (Other academic)
Abstract [en]

Sweden was a pioneering country in the development of NumericalWeather Prediction (NWP). The worlds first operational numerical forecast was produced already in 1954 by the International Meteorological Institute in Stockholm. SMHI started a bit later, but in 1961 a long term program for development of NWP was initiated. The activities grew gradually during the 1960’s and resulted in a core component for the SMHI forecast services. An early challenge was to overcome the limited computational resources with slow computational speed, small memory size and primitive software support. It was necessary to compensate for these limitations with dedicated work and creativity. A core component in this work was the software system MAC (Meteorological Auto Code) that was developed by the NWP group at SMHI. The MAC system is described in detail in this report and it included all computational software needed for the weather service, for example numerical models, objective analysis techniques, automatic data extraction, quality control of observations as well as forecast products in graphical or digital form.

We hope that this report will provide the younger generation with some insight into the conditions for development of NWP during the 1960’s.

Abstract [sv]

Sverige var ett föregångsland inom numeriska vädderprognoser och den allra första operativa väderprognosen gjordes redan 1954 på det Internationella Meteorologiska Institutet i Stockholm. SMHI kom igång senare, men 1961 startade man ett långsiktigt program för NWP (numerical weather prediction). Projektet växte gradvis under 1960-talet och blev så småningom en central komponent i SMHIs prognostjänst. En utmaning under de tidiga åren var de begränsade dataresurserna med primitiv programvara, och med dagens mått begränsat minnesutrymme och låg beräkningshastighet. För att kompensera dessa brister krävdes både beslutsamhet och ett stort mått av kreativitet. Som en central komponent i arbetet utvecklade NWP-gruppen datorsystemet MAC (Meteorological Auto Code) som här beskrivs i detalj samt också alla de beräkningsprogram som krävdes för prognostjänsten. Detta inkluderade olika prognosmodeller, analys samt program för databehandling och observationskontroll samt produktion av prognosresultaten i grafisk eller digital form.

Det är vår förhoppning att f´öreliggande artikel skall ge den yngre generationen en inblick i hur det var att syssla med NWP under 1960-talet.

Publisher
p. 21
Series
RMK: Report Meteorology and Climatology, ISSN 0347-2116 ; 117
National Category
Meteorology and Atmospheric Sciences Climate Research
Research subject
Meteorology; Climate
Identifiers
urn:nbn:se:smhi:diva-2152 (URN)
Available from: 2016-05-10 Created: 2016-05-10 Last updated: 2016-05-31Bibliographically approved
Blazica, V., Gustafsson, N. & Zagar, N. (2015). The impact of periodization methods on the kinetic energy spectra for limited-area numerical weather prediction models. Geoscientific Model Development, 8(1), 87-97
Open this publication in new window or tab >>The impact of periodization methods on the kinetic energy spectra for limited-area numerical weather prediction models
2015 (English)In: Geoscientific Model Development, ISSN 1991-959X, E-ISSN 1991-9603, Vol. 8, no 1, p. 87-97Article in journal (Refereed) Published
Abstract [en]

The paper deals with the comparison of the most common periodization methods used to obtain spectral fields of limited-area models for numerical weather prediction. The focus is on the impact that the methods have on the spectra of the fields, which are used for verification and tuning of the models. A simplified model is applied with random fields that obey a known kinetic energy spectrum. The periodization methods under consideration are detrending, the discrete cosine transform and the application of an extension zone. For the extension zone, three versions are applied: the Boyd method, the ALADIN method and the HIRLAM method. The results show that detrending and the discrete cosine transform have little impact on the spectra, as does the Boyd method for extension zone. For the ALADIN and HIRLAM methods, the impact depends on the width of the extension zone - the wider the zone, the more artificial energy and the larger impact on the spectra. The width of the extension zone correlates to the modifications in the shape of the spectra as well as to the amplitudes of the additional energy in the spectra.

National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-2014 (URN)10.5194/gmd-8-87-2015 (DOI)000348978400006 ()
Available from: 2016-04-06 Created: 2016-03-03 Last updated: 2017-11-30Bibliographically approved
Gustafsson, N., Bojarova, J. & Vignes, O. (2014). A hybrid variational ensemble data assimilation for the HIgh Resolution Limted Area Model (HIRLAM). Nonlinear processes in geophysics, 21(1), 303-323
Open this publication in new window or tab >>A hybrid variational ensemble data assimilation for the HIgh Resolution Limted Area Model (HIRLAM)
2014 (English)In: Nonlinear processes in geophysics, ISSN 1023-5809, E-ISSN 1607-7946, Vol. 21, no 1, p. 303-323Article in journal (Refereed) Published
Abstract [en]

A hybrid variational ensemble data assimilation has been developed on top of the HIRLAM variational data assimilation. It provides the possibility of applying a flow-dependent background error covariance model during the data assimilation at the same time as full rank characteristics of the variational data assimilation are preserved. The hybrid formulation is based on an augmentation of the assimilation control variable with localised weights to be assigned to a set of ensemble member perturbations (deviations from the ensemble mean). The flow-dependency of the hybrid assimilation is demonstrated in single simulated observation impact studies and the improved performance of the hybrid assimilation in comparison with pure 3-dimensional variational as well as pure ensemble assimilation is also proven in real observation assimilation experiments. The performance of the hybrid assimilation is comparable to the performance of the 4-dimensional variational data assimilation. The sensitivity to various parameters of the hybrid assimilation scheme and the sensitivity to the applied ensemble generation techniques are also examined. In particular, the inclusion of ensemble perturbations with a lagged validity time has been examined with encouraging results.

National Category
Geophysics
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-162 (URN)10.5194/npg-21-303-2014 (DOI)000332337700023 ()
Available from: 2015-03-31 Created: 2015-03-26 Last updated: 2017-12-04Bibliographically approved
Gustafsson, N. & Bojarova, J. (2014). Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM). Nonlinear processes in geophysics, 21(4), 745-762
Open this publication in new window or tab >>Four-dimensional ensemble variational (4D-En-Var) data assimilation for the HIgh Resolution Limited Area Model (HIRLAM)
2014 (English)In: Nonlinear processes in geophysics, ISSN 1023-5809, E-ISSN 1607-7946, Vol. 21, no 4, p. 745-762Article in journal (Refereed) Published
Abstract [en]

A four-dimensional ensemble variational (4D-EnVar) data assimilation has been developed for a limited area model. The integration of tangent linear and adjoint models, as applied in standard 4D-Var, is replaced with the use of an ensemble of non-linear model states to estimate four-dimensional background error covariances over the assimilation time window. The computational costs for 4D-En-Var are therefore significantly reduced in comparison with standard 4D-Var and the scalability of the algorithm is improved. The flow dependency of 4D-En-Var assimilation increments is demonstrated in single simulated observation experiments and compared with corresponding increments from standard 4D-Var and Hybrid 4D-Var ensemble assimilation experiments. Real observation data assimilation experiments carried out over a 6-week period show that 4D-En-Var outperforms standard 4D-Var as well as Hybrid 4D-Var ensemble data assimilation with regard to forecast quality measured by forecast verification scores.

National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-150 (URN)10.5194/npg-21-745-2014 (DOI)000340106000002 ()
Available from: 2015-04-08 Created: 2015-03-26 Last updated: 2017-12-04Bibliographically approved
Sundstrom, N., Gustafsson, N., Kruglyak, A. & Lundberg, A. (2013). Field evaluation of a new method for estimation of liquid water content and snow water equivalent of wet snowpacks with GPR. HYDROLOGY RESEARCH, 44(4), 600-613
Open this publication in new window or tab >>Field evaluation of a new method for estimation of liquid water content and snow water equivalent of wet snowpacks with GPR
2013 (English)In: HYDROLOGY RESEARCH, ISSN 1998-9563, Vol. 44, no 4, p. 600-613Article in journal (Refereed) Published
Abstract [en]

Estimates of snow water equivalent (SWE) with ground-penetrating radar can be used to calibrate and validate measurements of SWE over large areas conducted from satellites and aircrafts. However, such radar estimates typically suffer from low accuracy in wet snowpacks due to a built-in assumption of dry snow. To remedy the problem, we suggest determining liquid water content from path-dependent attenuation. We present the results of a field evaluation of this method which demonstrate that, in a wet snowpack between 0.9 and 3 m deep and with about 5 vol% of liquid water, liquid water content is underestimated by about 50% (on average). Nevertheless, the method decreases the mean error in SWE estimates to 16% compared to 34% when the presence of liquid water in snow is ignored and 31% when SWE is determined directly from two-way travel time and calibrated for manually measured snow density.

Keywords
ground-penetrating radar, liquid water content, path-dependent attenuation, radar wave propagation velocity, snow water equivalent, wet snow
National Category
Oceanography, Hydrology and Water Resources
Research subject
Hydrology
Identifiers
urn:nbn:se:smhi:diva-404 (URN)10.2166/nh.2012.182 (DOI)000321953200003 ()
Available from: 2015-04-01 Created: 2015-03-31 Last updated: 2018-01-11Bibliographically approved
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
Open this publication in new window or tab >>The impact of cloud-affected IR radiances on forecast accuracy of a limited-area NWP model
2013 (English)In: Quarterly Journal of the Royal Meteorological Society, ISSN 0035-9009, E-ISSN 1477-870X, Vol. 139, no 677, p. 2081-2096Article in journal (Refereed) 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.

Keywords
assimilation, cloudy radiances, numerical weather prediction, limited-area NWP model
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-344 (URN)10.1002/qj.2102 (DOI)000328348000010 ()
Available from: 2015-04-14 Created: 2015-03-31 Last updated: 2017-12-04Bibliographically approved
Dahlgren, P. & Gustafsson, N. (2012). Assimilating host model information into a limited area model. Tellus. Series A, Dynamic meteorology and oceanography, 64, Article ID 15836.
Open this publication in new window or tab >>Assimilating host model information into a limited area model
2012 (English)In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 64, article id 15836Article in journal (Refereed) Published
Abstract [en]

We propose to add an extra source of information to the data-assimilation of the regional HIgh Resolution Limited Area Model (HIRLAM) model, constraining larger scales to the host model providing the lateral boundary conditions. An extra term, J(k), measuring the distance to the large-scale vorticity of the host model, is added to the cost-function of the variational data-assimilation. Vorticity is chosen because it is a good representative of the large-scale flow and because vorticity is a basic control variable of the HIRLAM variational data-assimilation. Furthermore, by choosing only vorticity, the remaining model variables, divergence, temperature, surface pressure and specific humidity will be allowed to adapt to the modified vorticity field in accordance with the internal balance constraints of the regional model. The error characteristics of the J(k) term are described by the horizontal spectral densities and the vertical eigenmodes (eigenvectors and eigenvalues) of the host model vorticity forecast error fields, expressed in the regional model geometry. The vorticity field, provided by the European Centre for Medium-range Weather Forecasts (ECMWF) operational model, was assimilated into the HIRLAM model during an experiment period of 33 d in winter with positive impact on forecast verification statistics for upper air variables and mean sea level pressure.

Keywords
data-assimilation, large-scale constraint, error covariances, limited area, host model
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-489 (URN)10.3402/tellusa.v64i0.15836 (DOI)000300394900001 ()
Available from: 2015-04-14 Created: 2015-04-14 Last updated: 2017-12-04Bibliographically approved
Gustafsson, N. (2012). Control of lateral boundary conditions in four-dimensional variational data assimilation for a limited area model. Tellus. Series A, Dynamic meteorology and oceanography, 64, Article ID 17518.
Open this publication in new window or tab >>Control of lateral boundary conditions in four-dimensional variational data assimilation for a limited area model
2012 (English)In: Tellus. Series A, Dynamic meteorology and oceanography, ISSN 0280-6495, E-ISSN 1600-0870, Vol. 64, article id 17518Article in journal (Refereed) Published
Abstract [en]

The limited area model forecasting problem is a lateral boundary condition (LBC) problem in addition to the initial condition problem. The data assimilation has traditionally been considered as a process for estimation of the initial condition only, while for the limited area data assimilation this estimation may be extended to include also the LBCs, at least during the data assimilation time window when observations are available. A procedure for such a control of the LBCs has been included in the four-dimensional variational data assimilation (4D-Var) scheme for the HIgh Resolution Limited Area Model (HIRLAM) forecasting system. A description of this procedure is provided together with results from idealised as well as real data experiments. The results indicate that control of LBCs may be important with small forecast domains and in particular for weather disturbances moving quickly into and through the forecast domain.

Keywords
data assimilation, lateral boundary conditions
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:smhi:diva-486 (URN)10.3402/tellusa.v64i0.17518 (DOI)000302383500001 ()
Available from: 2015-04-15 Created: 2015-04-14 Last updated: 2017-12-04Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8376-2729

Search in DiVA

Show all publications
v. 2.35.6
|