9:45 AM - 10:00 AM
[MIS01-04] Soil composition impact on long-range weather forecasts over Northern Eurasia using SL-AV model
★Invited Papers
Keywords:long-range weather forecasts, soil composition, heatwaves
The problem of predicting heat waves during the warm season in North Eurasia attracts much attention last years (Domeisen et al., 2023). They cut crop yields, cause devastating forest fires, human losses and other ecological and economic damages, e.g. Russian heatwave of July-August 2010 (Katsafados et al., 2014).
SL-AV is the global atmospheric model used for medium-range, subseasonal and seasonal forecasts at Hydrometeorological Research Center of Russia (Tolstykh et al., 2018). Soil processes in SL-AV are represented by multilayer soil model INM RAS-MSU (Volodin and Lykosov, 1998) with module of observations assimilation (Travova and Tolstykh 2022).
The effect of including two different global soil composition datasets on reproduction of soil processes is investigated. Some model experiments are calculated: with soil particle size distribution and type obtained from the ECOCLIMAP database and with the respective fields from Global Soil Dataset for use in Earth System Models (GSDE) database. Unique in situ soil temperature and moisture data of Russian agrometeorological stations for the 5 years are used to estimate results.
Numerical ensemble experiments are carried out to assess the sensitivity of long-range forecasts of the SL-AV model to replacement of ECOCLIMAP data with the fields from GSDE database. Two series of long-range forecasts for July with two different soil compositions are performed, with initial data from April 30 and the ensemble size of 12. The period from 1991 to 2015 is chosen as the reference one. To analyze the sensitivity of ensemble long-term forecasts to changes in soil granulometric composition, three anomalous heat waves are selected: July 1998 (Russia), July 2003 (Northern and Southern Europe), and July 2010 (Eastern Europe and the European part of Russia).
The long-term prediction of abnormal heat waves in the Northern Hemisphere by the SL-AV model proves to be sensitive to the granulometric composition of soil. The use of new soil fields allows to predict correctly the sign of temperature and geopotential field anomalies in situations of extreme events. The effects of the ensemble size and stochastic parameters perturbation of model parameters on the predictions are studied.
This research was carried out at the Hydrometcentre of Russia with the support of Russian Science Foundation No. 21-17-00254.
References
Domeisen D.I.V., Eltahir E.A.B., Fischer E.M. et al. (2023) Prediction and projection of heatwaves. Nat Rev Earth Environ 4, 36–50. DOI: 10.1038/s43017-022-00371-z
Katsafados P., Papadopoulus A., Varlas G., Papadopoulou E. and Mavromatidis E. (2014) Seasonal predictability of the 2010 Russian heat wave. Nat. Hazards Earth Syst. Sci., 14, 1531–1542. DOI: 10.5194/nhess-14-1531-2014
Tolstykh M.A., Fadeev R.Yu., Shashkin V.V., Goyman G.S., Zaripov R.B., Kiktev D.B., Makhnorylova S.V., Mizyak V.G., Rogutov V.S. (2018) Multiscale global atmosphere model SL-AV: The results of medium-range weather forecasts. Russ. Meteorol. Hydrol. 43, 773–786. DOI: 10.3103/S1068373918110080
Volodin E.M. and V. N. Lykosov V.N. (1998) Parameterization of Heat and Moisture Processes in Soil–Vegetation System. 1. Description and Calculations Using Local Observational Data. Izv., Atmos. Oceanic Phys., No. 4, 34
Travova S.V., Tolstykh M.A. (2022) Assimilation of Screen-level Observations for Soil Moisture Analysis in the INM RAS-MSU Multilayer Soil Model Included in the SL-AV Global Atmospheric Modeling System. Russ. Meteorol. Hydrol. 47, 561. DOI: 10.3103/S1068373922080015
SL-AV is the global atmospheric model used for medium-range, subseasonal and seasonal forecasts at Hydrometeorological Research Center of Russia (Tolstykh et al., 2018). Soil processes in SL-AV are represented by multilayer soil model INM RAS-MSU (Volodin and Lykosov, 1998) with module of observations assimilation (Travova and Tolstykh 2022).
The effect of including two different global soil composition datasets on reproduction of soil processes is investigated. Some model experiments are calculated: with soil particle size distribution and type obtained from the ECOCLIMAP database and with the respective fields from Global Soil Dataset for use in Earth System Models (GSDE) database. Unique in situ soil temperature and moisture data of Russian agrometeorological stations for the 5 years are used to estimate results.
Numerical ensemble experiments are carried out to assess the sensitivity of long-range forecasts of the SL-AV model to replacement of ECOCLIMAP data with the fields from GSDE database. Two series of long-range forecasts for July with two different soil compositions are performed, with initial data from April 30 and the ensemble size of 12. The period from 1991 to 2015 is chosen as the reference one. To analyze the sensitivity of ensemble long-term forecasts to changes in soil granulometric composition, three anomalous heat waves are selected: July 1998 (Russia), July 2003 (Northern and Southern Europe), and July 2010 (Eastern Europe and the European part of Russia).
The long-term prediction of abnormal heat waves in the Northern Hemisphere by the SL-AV model proves to be sensitive to the granulometric composition of soil. The use of new soil fields allows to predict correctly the sign of temperature and geopotential field anomalies in situations of extreme events. The effects of the ensemble size and stochastic parameters perturbation of model parameters on the predictions are studied.
This research was carried out at the Hydrometcentre of Russia with the support of Russian Science Foundation No. 21-17-00254.
References
Domeisen D.I.V., Eltahir E.A.B., Fischer E.M. et al. (2023) Prediction and projection of heatwaves. Nat Rev Earth Environ 4, 36–50. DOI: 10.1038/s43017-022-00371-z
Katsafados P., Papadopoulus A., Varlas G., Papadopoulou E. and Mavromatidis E. (2014) Seasonal predictability of the 2010 Russian heat wave. Nat. Hazards Earth Syst. Sci., 14, 1531–1542. DOI: 10.5194/nhess-14-1531-2014
Tolstykh M.A., Fadeev R.Yu., Shashkin V.V., Goyman G.S., Zaripov R.B., Kiktev D.B., Makhnorylova S.V., Mizyak V.G., Rogutov V.S. (2018) Multiscale global atmosphere model SL-AV: The results of medium-range weather forecasts. Russ. Meteorol. Hydrol. 43, 773–786. DOI: 10.3103/S1068373918110080
Volodin E.M. and V. N. Lykosov V.N. (1998) Parameterization of Heat and Moisture Processes in Soil–Vegetation System. 1. Description and Calculations Using Local Observational Data. Izv., Atmos. Oceanic Phys., No. 4, 34
Travova S.V., Tolstykh M.A. (2022) Assimilation of Screen-level Observations for Soil Moisture Analysis in the INM RAS-MSU Multilayer Soil Model Included in the SL-AV Global Atmospheric Modeling System. Russ. Meteorol. Hydrol. 47, 561. DOI: 10.3103/S1068373922080015