The report describes todays and future climate in Stockholm County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
The report describes todays and future climate in Södermanland County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
The report describes todays and future climate in Östergötland County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
Calculations have been made for how the water release, water abstraction, water temperature and ice extent are expected to change in Lake Hjälmaren up to the year 2100 due to global warming.The most noticeable effects of the future climate on Lake Hjälmaren are expected to be:
The water level in Lake Hjälmaren is only expected to change by a small amount in the future climate. The most obvious change is that low water levels will be more frequent, especially during the summer and autumn. This is due to an expected increase in evaporation, both from vegetation in the lake’s catchment area and from the surface of the lake. Currently the water level is lower than 21.6 m for about one month per year onaverage. In the future the water level is expected to be lower than 21.6 m for about 3.5 months.For the highest water levels (calculated maximum water level) an increase is shown for the high emission scenario (RCP8.5) while changes are expected to be small for the scenario with limited emission of greenhouse gases (RCP4.5).The water temperature in Lake Hjälmaren is expected to increase by about half a degree by the middle of the century and by 1 to 2.5 degrees by the end of the century. The number of days per year where the surface water temperature exceeds 20 degrees is expected to increase from the current value of around 7 weeks per year to about 9 weeks per year by the middle of the century and up to 12 weeks per year by the end of the century. Currently Lake Hjälmaren is covered with ice every winter. In the future climate it is expected that there will be some winters without ice coverage.
Beräkningar har gjorts för hur vattennivåer, tappningar, vattentemperatur och is beräknas förändras i Vänern fram till 2100 på grund av den globala uppvärmningen. De tydligaste förändringarna i Vänern och Göta älv i ett framtida klimat beräknas bli att: Det blir vanligare med låga nivåer i Vänern. Det blir vanligare med höga nivåer i Vänern. Det blir vanligare med låga tappningar i Göta älv. Det blir vanligare med höga tappningar i Göta älv. Det blir högre vattentemperaturer. Det blir kortare perioder med is. I denna rapport redovisas nya beräkningar för Vänerns nivåer som ersätter de tidigare beräkningarna från 2010 (Bergström m.fl. 2010).
Calculations have been made for how the water level, water release, water temperature and ice extent are expected to change in Lake Vättern up to the year 2100 due to global warming.The most noticeable effects of the future climate on Lake Vättern are expected to be:
With a warmer climate the evaporation is expected to increase, both from vegetation in the lake’s catchment area as well as directly from the surface of the lake. This means that the water level in Lake Vättern is expected to be lower in the future. Calculations show that the average water level in Lake Vättern is expected to drop by one to two decimetres by the end of the century, with about the same reduction for all seasons.The number of days per year where the water level is below 88.3 m is expected to increase from the present value of around 1.5 months to about 3 months by the middle of the century and 4-6 months by the end of the century. The highest levels, the calculated maximum water level, are expected to remain unchanged in the future.
Rapporten är en utvärdering av SMHI:s hydrologiska prognos- och varningstjänsts arbete 26 oktober 2006-19 januari 2007 med flödessituationen i sydvästra Sverige. I dokumentet beskrivs även den hydrologiska situationen för den aktuella tiden.Det höga flödet uppkom på grund av en blöt höst och förvinter i södra Sverige. Det milda vädret med riklig nederbörd fortsatte sedan under första delen av januari och orsakade en andra flödestopp på många ställen. Med hjälp av observationer i realtid, meteorologiska prognoser, hydrologiska, prognoser, visualiseringsverktyg och ett nära samarbete med kraftbolagen är SMHI:s hydrologiska prognos- och varningstjänst kontinuerligt uppdaterad på det hydrologiska läget i hela Sverige. När sannolikheten bedöms vara större än 50 % för att en varningsnivå överskrids skall en varning utfärdas. Under mycket höga flöden skall SMHI också stötta länsstyrelse och räddningstjänst med meteorologisk och hydrologisk expertis samt med specialanpassade prognoser.SMHI gör dagligen automatiska prognoser för över 80 st utvalda avrinningsområden i Sverige. Under det aktuella flödet utfördes ett antal manuella specialanpassade prognoser med högre kvalitet för det drabbade området. Generellt var prognoserna av god kvalitet, men på vissa ställen blev prognoserna sämre på grund av olika orsaker. Under flödet lade SMHI ned ca 1100 arbetstimmar utöver det som är normalt för perioden.SMHI har under perioden skickat ut 38 flödesvarningar och 12 hydrologiska informationer. Utvärdering av årets hydrologiska varningars träffsäkerhet görs i november varje år och ingår därför inte i denna rapport. Efter flödet skickades en enkät ut till de kommuner, länsstyrelser och kraftbolag som berördes av varningarna. Enkäten avsåg perioden nov 2006-dec 2006. En sammanställning av enkätsvaren och samtliga kommentarer redovisas i denna rapport. Det övergripande omdömet om SMHI:s tjänster var positivt.
A system for ensemble streamflow prediction, ESP, has been operational at SMHI since July 2004, based on 50 meteorological ensemble forecasts from ECMWF. Hydrological ensemble forecasts are produced daily for 51 basins in Sweden. All ensemble members, as well as statistics (minimum, 25% quartile, median, 75% quartile and maximum), are stored in a database. This paper presents an evaluation of the first 18 months of ESP median forecasts from this system, and in particular their performance in comparison with today's categorical forecast. The evaluation was made in terms of three statistical measures: bias B, root mean square error RMSE and absolute peak flow error PE. For ESP forecasts the bias ranged between -20% and 80% with a systematic overestimation for Sweden as a whole. A comparison between bias in input precipitation and ESP output, respectively, revealed only a weak relationship, but streamflow overestimation is likely related mainly to model properties. The results from the streamflow forecast comparison showed that the ESP median in deterministic terms performs overall as well as the presently used categorical forecast. Further, ESP has the advantage of providing at least a qualitative measure of the uncertainty in the forecasts, with probability forecasts being the ultimate goal.
Mellan den 16 januari och 13 februari föll rikligt med regn över sydvästra Sverige. I kombination med viss snösmältning orsakade detta kraftigt stigande flöden och översvämningar som följd. Flödena kulminerade på många håll i början av februari. I slutet av februari och början av mars ökade återigen flödena kraftigt till följd av nya regnväder. På de flesta håll nåddes dock inte flöden lika höga som i början av februari.
The report describes todays and future climate in Blekinge County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
The report describes todays and future climate in Jönköping County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
The report describes todays and future climate in Skåne County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
The report describes todays and future climate in Västmanland County based on observations and climate modelling. Regional modelled RCP4.5 and RCP8.5 scenarios have been further downscaled to 4×4 km2 resolution. The results are presented as meteorological and hydrological indices based on statistically processed model data.
Since July 2004, a system for hydrological ensemble forecasting has been operational at SMHI. The system uses meteorological ensemble forecasts of precipitation and temperature from ECMWF as input to the hydrological HBV model, which generates an ensemble of discharge forecasts. In this report, the hydrological ensemble prediction system (EPS) is firstly described, along with some general features of the forecasts. Some preparatory analyses of the ECMWF meteorological forecasts and spring flood EPS forecasts are made. The main part of the report is an evaluation of 18 months of 9-day hydrological ensemble forecasts in 45 Swedish catchments. In the deterministic evaluation, the EPS median forecast is compared with the categorical PMP forecast. The results indicate an overall similar performance of the two forecast types. It is also shown that the spread of the EPS forecasts is related to the forecast error. In the probabilistic evaluation, the accuracy of probabilities calculated from the EPS spread is investigated. A percentile-based evaluation shows that the spread is underestimated. A threshold-based evaluation shows that the probability of exceeding some high discharge threshold level is overestimated. Finally, a simple method to correct the EPS spread is developed and tested, and different ways to present EPS forecasts are discussed.
Flood maps for return periods 100-years and 250-years together with a calculated highest flow have been produced for the lower part of the River Torne. The work was made within the Interreg IV A Nord Project “Detailed flood mapping of the lower part of River Torne”. Flows with return periods 100-years and 250-years were calculated statistically based on observations. The calculated highest flow was modeled with the hydrological HBV-model according to the Swedish design flood guidelines (Flood Design Category I). A hydraulic model was built to calculate water levels along the river at the different flow levels. The model was based on height data from laser scanning and river bottom data from sounding. The data sampling was made in cooperation between Swedish and Finnish authorities within the project. The flood zones were projected on background map data from the national land services in Finland and Sweden. The area was divided in nine parts and mapped with scaling 1: 75 000. The maps are available at www.smhi.se in original size and collected in appendix (bilaga 1) in a compressed form. SMHI sounded half of the investigated river length. SMHI was responsible for and performed the hydraulic modeling, flow calculations and production of flood zones and maps.
The county analyzes (Sjökvist et al. 2015) were published by SMHI in 2015 with the aim to produce county-wise climate data based on results from the IPCC's fifth assessment report (AR5, 2013). In 2021, SMHI published a new climate scenario web service (www.smhi.se/klimat), containing updated data from climate research. As both the methodology, calculation methods and level of detail have been developed and updated, differences between the results in the county analyzes and the scenario service are expected. This report aims to clarify the differences between the two datasets and explain what these differences are due to, in support of old and new users of SMHI's climate data.