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Abstract
The 2000 tropical cyclone season over the South Indian Ocean (SIO) was exceptional in terms of tropical cyclone landfall over Mozambique. Observed data suggest that SIO tropical cyclones have a track significantly more zonal during a La Niña event and tend to be more frequent when local SSTs are warmer. The combination of both conditions happened during the 2000 SIO tropical cyclone season and may explain the exceptional number of tropical cyclone landfalls over Mozambique during that season. A set of experiments using an atmospheric model of fairly high resolution (T L 159, with a Gaussian grid spacing of 1.125°) forced by prescribed SSTs confirms the role of La Niña conditions and warmer local SSTs on the frequency of tropical cyclone landfalls over Mozambique. This also suggests that a numerical model can simulate the mechanisms responsible for the exceptional 2000 tropical cyclone season, and therefore could be used to explicitly predict the risk of landfall over Mozambique.
A coupled model with a T L 159 atmospheric component has been integrated for 3 months starting on 1 January of each year 1987–2001 to test this hypothesis. The hindcast produces significantly more tropical cyclone landfalls in 2000 than in any other year, and years with a predicted high risk of landfall generally coincide with years of observed tropical cyclone landfall.
Abstract
The 2000 tropical cyclone season over the South Indian Ocean (SIO) was exceptional in terms of tropical cyclone landfall over Mozambique. Observed data suggest that SIO tropical cyclones have a track significantly more zonal during a La Niña event and tend to be more frequent when local SSTs are warmer. The combination of both conditions happened during the 2000 SIO tropical cyclone season and may explain the exceptional number of tropical cyclone landfalls over Mozambique during that season. A set of experiments using an atmospheric model of fairly high resolution (T L 159, with a Gaussian grid spacing of 1.125°) forced by prescribed SSTs confirms the role of La Niña conditions and warmer local SSTs on the frequency of tropical cyclone landfalls over Mozambique. This also suggests that a numerical model can simulate the mechanisms responsible for the exceptional 2000 tropical cyclone season, and therefore could be used to explicitly predict the risk of landfall over Mozambique.
A coupled model with a T L 159 atmospheric component has been integrated for 3 months starting on 1 January of each year 1987–2001 to test this hypothesis. The hindcast produces significantly more tropical cyclone landfalls in 2000 than in any other year, and years with a predicted high risk of landfall generally coincide with years of observed tropical cyclone landfall.
Abstract
The physics of the Indo–Pacific warm pool are investigated using a coupled ocean atmosphere general circulation model. The model, developed at the Max-Planck-Institut fair Meteorologic, Hamburg, does not employ a flux correction and is used with atmospheres at T42 and T21 resolution. The simulations are compared with observations, and the model's mean and seasonal heat budgets and physics in the Indo–Pacific warm pool region are explored for the T42 resolution run.
Despite the simulation of a split intertropical convergence zone, and of a cold tongue that extends too far to the west, simulated warm pool temperatures are consistent with observations at T42 resolution, while the T21 resolution yields a cold bias of 1K. At T42 resolution the seasonal migration of the warm pool is reproduced reasonably well, as are the surface heat fluxes, winds, and clouds. However, simulated precipitation is too small compared to observations, implying that the surface density flux is dominated by fluxes of heat.
In the Pacific portion of the warm pool, the average net heat gain of the ocean amounts to 30–40 W m−2. In the northern branch, this heat gain is balanced by vertical advection, while in the southern branch, zonal, meridional, and vertical advection cool the ocean at approximately equal rates. At the equator, the surface heat flux is balanced by zonal and vertical advection and vertical mixing. The Indonesian and Indian Ocean portions of the warm pool receive from the atmosphere 30 and 50 W m−2, respectively, and this flux is balanced by vertical advection. The cooling due to vertical advection stems from numerical diffusion associated with the upstream scheme, the coarse vertical resolution of the ocean model, and near-inertial oscillations forced by high-frequency atmospheric variability.
The seasonal migration of the warm pool is largely a result of the seasonal variability of the net surface heat flux, horizontal and vertical advections are of secondary importance and increase the seasonal range of surface temperature slightly everywhere in the warm pool, with the exception of its southern branch. There, advection reduces the effect of the surface flux. The seasonal variability of the surface heat flux in turn is mainly determined by the shortwave radiation, but evaporation modifies the signal significantly. The annual cycles of reduction of solar radiation due to clouds and SST evolve independently from each other in the Pacific portion of the warm pool; that is, clouds have little impact on SST. In the Indian Ocean, however, clouds limit the maximum SST attained during the annual cycle.
In the western Pacific and Indonesian portion of the warm pool, penetrative shortwave radiation leads to convective mixing by heating deeper levels at a greater rate than the surface, which experiences heat losses due to turbulent and longwave heat fluxes. In the deeper levels, there is no mechanism to balance the heating due to penetrative radiation, except convection and its attendant mixing. In the Indian Ocean, however. the resulting vertical heating profile due to the surface fluxes decreases monotonically with depth and does not support convective mixing. Concurrently, the warm pool is shallower in the Indian Ocean compared with the western Pacific, indicating that convective mixing due to penetrative radiation is important in maintaining the vertical structure of the Pacific portion of the warm pool.
Abstract
The physics of the Indo–Pacific warm pool are investigated using a coupled ocean atmosphere general circulation model. The model, developed at the Max-Planck-Institut fair Meteorologic, Hamburg, does not employ a flux correction and is used with atmospheres at T42 and T21 resolution. The simulations are compared with observations, and the model's mean and seasonal heat budgets and physics in the Indo–Pacific warm pool region are explored for the T42 resolution run.
Despite the simulation of a split intertropical convergence zone, and of a cold tongue that extends too far to the west, simulated warm pool temperatures are consistent with observations at T42 resolution, while the T21 resolution yields a cold bias of 1K. At T42 resolution the seasonal migration of the warm pool is reproduced reasonably well, as are the surface heat fluxes, winds, and clouds. However, simulated precipitation is too small compared to observations, implying that the surface density flux is dominated by fluxes of heat.
In the Pacific portion of the warm pool, the average net heat gain of the ocean amounts to 30–40 W m−2. In the northern branch, this heat gain is balanced by vertical advection, while in the southern branch, zonal, meridional, and vertical advection cool the ocean at approximately equal rates. At the equator, the surface heat flux is balanced by zonal and vertical advection and vertical mixing. The Indonesian and Indian Ocean portions of the warm pool receive from the atmosphere 30 and 50 W m−2, respectively, and this flux is balanced by vertical advection. The cooling due to vertical advection stems from numerical diffusion associated with the upstream scheme, the coarse vertical resolution of the ocean model, and near-inertial oscillations forced by high-frequency atmospheric variability.
The seasonal migration of the warm pool is largely a result of the seasonal variability of the net surface heat flux, horizontal and vertical advections are of secondary importance and increase the seasonal range of surface temperature slightly everywhere in the warm pool, with the exception of its southern branch. There, advection reduces the effect of the surface flux. The seasonal variability of the surface heat flux in turn is mainly determined by the shortwave radiation, but evaporation modifies the signal significantly. The annual cycles of reduction of solar radiation due to clouds and SST evolve independently from each other in the Pacific portion of the warm pool; that is, clouds have little impact on SST. In the Indian Ocean, however, clouds limit the maximum SST attained during the annual cycle.
In the western Pacific and Indonesian portion of the warm pool, penetrative shortwave radiation leads to convective mixing by heating deeper levels at a greater rate than the surface, which experiences heat losses due to turbulent and longwave heat fluxes. In the deeper levels, there is no mechanism to balance the heating due to penetrative radiation, except convection and its attendant mixing. In the Indian Ocean, however. the resulting vertical heating profile due to the surface fluxes decreases monotonically with depth and does not support convective mixing. Concurrently, the warm pool is shallower in the Indian Ocean compared with the western Pacific, indicating that convective mixing due to penetrative radiation is important in maintaining the vertical structure of the Pacific portion of the warm pool.
Abstract
This paper describes the assessment of the performance of a method for providing early warnings of unusually wet and dry precipitation conditions globally. The indicator that is used for forecasting these conditions is computed from forecasted standardized precipitation index (SPI) values for accumulation periods of 1, 3, and 6 months. The SPI forecasts are derived from forecasted precipitation produced by the latest probabilistic seasonal forecast of ECMWF. Early warnings of unusual precipitation periods are shown only when and where the forecast is considered robust (i.e., with at least 40% of ensemble members associated with intense forecasts), and corresponding with significant SPI values (i.e., below −1 for dry, or above +1 for wet conditions). The intensity of the forecasted events is derived based on the extreme forecast index and associated shift of tails products developed by ECMWF. Different warning levels are then assessed, depending on the return period of the forecast intensity, and the coherence of the ensemble forecast members. The assessment of the indicators performance is based on the 25-member ensemble forecast system that is carried out every month during the 36 years of the hindcast period (1981–2016). The results show that significant information is provided even for the longest lead time, albeit with a large variability across the globe with the highest scores over central Russia, Southeast Asia, and the northern part of South America or Australia. Because of the loss of predictability, each SPI is based on the first lead time. A sensitivity test highlights the influence on the robustness of the forecasts of the warning levels used, as well as the effects of prior conditions and of seasonality.
Abstract
This paper describes the assessment of the performance of a method for providing early warnings of unusually wet and dry precipitation conditions globally. The indicator that is used for forecasting these conditions is computed from forecasted standardized precipitation index (SPI) values for accumulation periods of 1, 3, and 6 months. The SPI forecasts are derived from forecasted precipitation produced by the latest probabilistic seasonal forecast of ECMWF. Early warnings of unusual precipitation periods are shown only when and where the forecast is considered robust (i.e., with at least 40% of ensemble members associated with intense forecasts), and corresponding with significant SPI values (i.e., below −1 for dry, or above +1 for wet conditions). The intensity of the forecasted events is derived based on the extreme forecast index and associated shift of tails products developed by ECMWF. Different warning levels are then assessed, depending on the return period of the forecast intensity, and the coherence of the ensemble forecast members. The assessment of the indicators performance is based on the 25-member ensemble forecast system that is carried out every month during the 36 years of the hindcast period (1981–2016). The results show that significant information is provided even for the longest lead time, albeit with a large variability across the globe with the highest scores over central Russia, Southeast Asia, and the northern part of South America or Australia. Because of the loss of predictability, each SPI is based on the first lead time. A sensitivity test highlights the influence on the robustness of the forecasts of the warning levels used, as well as the effects of prior conditions and of seasonality.
Determining how El Niño and its impacts may change over the next 10 to 100 years remains a difficult scientific challenge. Ocean-atmosphere coupled general circulation models (CGCMs) are routinely used both to analyze El Niño mechanisms and teleconnections and to predict its evolution on a broad range of time scales, from seasonal to centennial. The ability to simulate El Niño as an emergent property of these models has largely improved over the last few years. Nevertheless, the diversity of model simulations of present-day El Niño indicates current limitations in our ability to model this climate phenomenon and to anticipate changes in its characteristics. A review of the several factors that contribute to this diversity, as well as potential means to improve the simulation of El Niño, is presented.
Determining how El Niño and its impacts may change over the next 10 to 100 years remains a difficult scientific challenge. Ocean-atmosphere coupled general circulation models (CGCMs) are routinely used both to analyze El Niño mechanisms and teleconnections and to predict its evolution on a broad range of time scales, from seasonal to centennial. The ability to simulate El Niño as an emergent property of these models has largely improved over the last few years. Nevertheless, the diversity of model simulations of present-day El Niño indicates current limitations in our ability to model this climate phenomenon and to anticipate changes in its characteristics. A review of the several factors that contribute to this diversity, as well as potential means to improve the simulation of El Niño, is presented.
Abstract
This paper is an evaluation of the role of salinity in the framework of temperature data assimilation in a global ocean model that is used to initialize seasonal climate forecasts. It is shown that the univariate assimilation of temperature profiles, without attempting to correct salinity, can induce first-order errors in the subsurface temperature and salinity fields. A recently developed scheme by A. Troccoli and K. Haines is used to improve the salinity field. In this scheme, salinity increments are derived from the observed temperature, by using the model temperature and salinity profiles, assuming that the temperature–salinity relationship in the model profiles is preserved. In addition, the temperature and salinity fields are matched below the observed temperature profile by vertically displacing the original model profiles.
Two data assimilation experiments were performed for the 6-yr period 1993–98. These show that the salinity scheme is effective at maintaining the haline and thermal structures at and below thermocline level, especially in tropical regions, by avoiding spurious convection. In addition to improvements in the mean state, the scheme allows more temporal variability than simply controlling the salinity field by relaxation to climatological data. Some comparisons with sparse salinity observations are also made, which suggest that the subsurface salinity variability in the western Pacific is better reproduced in the experiment in which the salinity scheme is used. The salinity analyses might be improved further by use of altimeter sea level or sea surface salinity observations from satellite.
Abstract
This paper is an evaluation of the role of salinity in the framework of temperature data assimilation in a global ocean model that is used to initialize seasonal climate forecasts. It is shown that the univariate assimilation of temperature profiles, without attempting to correct salinity, can induce first-order errors in the subsurface temperature and salinity fields. A recently developed scheme by A. Troccoli and K. Haines is used to improve the salinity field. In this scheme, salinity increments are derived from the observed temperature, by using the model temperature and salinity profiles, assuming that the temperature–salinity relationship in the model profiles is preserved. In addition, the temperature and salinity fields are matched below the observed temperature profile by vertically displacing the original model profiles.
Two data assimilation experiments were performed for the 6-yr period 1993–98. These show that the salinity scheme is effective at maintaining the haline and thermal structures at and below thermocline level, especially in tropical regions, by avoiding spurious convection. In addition to improvements in the mean state, the scheme allows more temporal variability than simply controlling the salinity field by relaxation to climatological data. Some comparisons with sparse salinity observations are also made, which suggest that the subsurface salinity variability in the western Pacific is better reproduced in the experiment in which the salinity scheme is used. The salinity analyses might be improved further by use of altimeter sea level or sea surface salinity observations from satellite.
Abstract
The first multimodel study to estimate the predictability of a boreal sudden stratospheric warming (SSW) is performed using five NWP systems. During the 2012/13 boreal winter, anomalous upward propagating planetary wave activity was observed toward the end of December, which was followed by a rapid deceleration of the westerly circulation around 2 January 2013, and on 7 January 2013 the zonal-mean zonal wind at 60°N and 10 hPa reversed to easterly. This stratospheric dynamical activity was followed by an equatorward shift of the tropospheric jet stream and by a high pressure anomaly over the North Atlantic, which resulted in severe cold conditions in the United Kingdom and northern Europe. In most of the five models, the SSW event was predicted 10 days in advance. However, only some ensemble members in most of the models predicted weakening of westerly wind when the models were initialized 15 days in advance of the SSW. Further dynamical analysis of the SSW shows that this event was characterized by the anomalous planetary wavenumber-1 amplification followed by the anomalous wavenumber-2 amplification in the stratosphere, which resulted in a split vortex occurring between 6 and 8 January 2013. The models have some success in reproducing wavenumber-1 activity when initialized 15 days in advance, but they generally failed to produce the wavenumber-2 activity during the final days of the event. Detailed analysis shows that models have reasonably good skill in forecasting tropospheric blocking features that stimulate wavenumber-2 amplification in the troposphere, but they have limited skill in reproducing wavenumber-2 amplification in the stratosphere.
Abstract
The first multimodel study to estimate the predictability of a boreal sudden stratospheric warming (SSW) is performed using five NWP systems. During the 2012/13 boreal winter, anomalous upward propagating planetary wave activity was observed toward the end of December, which was followed by a rapid deceleration of the westerly circulation around 2 January 2013, and on 7 January 2013 the zonal-mean zonal wind at 60°N and 10 hPa reversed to easterly. This stratospheric dynamical activity was followed by an equatorward shift of the tropospheric jet stream and by a high pressure anomaly over the North Atlantic, which resulted in severe cold conditions in the United Kingdom and northern Europe. In most of the five models, the SSW event was predicted 10 days in advance. However, only some ensemble members in most of the models predicted weakening of westerly wind when the models were initialized 15 days in advance of the SSW. Further dynamical analysis of the SSW shows that this event was characterized by the anomalous planetary wavenumber-1 amplification followed by the anomalous wavenumber-2 amplification in the stratosphere, which resulted in a split vortex occurring between 6 and 8 January 2013. The models have some success in reproducing wavenumber-1 activity when initialized 15 days in advance, but they generally failed to produce the wavenumber-2 activity during the final days of the event. Detailed analysis shows that models have reasonably good skill in forecasting tropospheric blocking features that stimulate wavenumber-2 amplification in the troposphere, but they have limited skill in reproducing wavenumber-2 amplification in the stratosphere.
