Gerrit Burgers

Analysis Scheme in the Ensemble Kalman Filter

This paper discusses an important issue related to the implementation and interpretation of the analysis scheme in the ensemble Kalman filter. It is shown that the observations must be treated as random variables at the analysis steps. That is, one should add random perturbations with the correct statistics to the observations and generate an ensemble of observations that then is used in updating the ensemble of model states. Traditionally, this has not been done in previous applications of the ensemble Kalman filter and, as will be shown, this has resulted in an updated ensemble with a variance that is too low. This simple modification of the analysis scheme results in a completely consistent approach if the covariance of the ensemble of model states is interpreted as the prediction error covariance, and there are no further requirements on the ensemble Kalman filter method, except for the use of an ensemble of sufficient size. Thus, there is a unique correspondence between the error statistics from the ensemble Kalman filter and the standard Kalman filter approach.

The “normality” of El Niño

The amplitude of the El Nino-Southern Oscillation (ENSO) would be normally distributed if the coupled Pacific ocean-atmosphere were a linear system forced by Gaussian weather noise. Moment estimates of skewness and kurtosis demonstrate that this is not the case for monthly mean anomalies in Pacific sea surface temperatures during 1950–97. The noted predominance of El Nino events compared to La Nina events is related to the high skewness in the eastern Pacific. Skewness and kurtosis both exhibit an intriguing geographical variation from positive in the eastern to negative in the western Pacific. We have also examined Nino-3 indices generated by three climate models having widely different complexity. These exhibit a wide range of skewness and kurtosis values rather different from those found for the observations. Skewness and kurtosis can be used to diagnose non-linear processes and provide powerful tools for validating models, and for testing observed sea-surface temperatures for the presence of possible climate change.

On the El Niño teleconnection to spring precipitation in Europe

In a statistical analysis of more than a century of data, a strong connection was found between strong warm El Nino winter events and high spring precipitation in a band from southern England eastwards into Asia. This relationship is an extension of the connection mentioned by Kiladis and Diaz (1989. ‘Global climatic anomalies associated with extremes in the Southern Oscillation’, J. Climate, 2, 1069–1090), and is much stronger than the winter season teleconnection that has been the subject of other studies. Correlation coefficients between December–January (DJF) NINO3 indices and March–May (MAM) precipitation are higher than r=0.3 for individual stations, and as high as r=0.49 for an index of precipitation anomalies around 50°N from 5°W to 35°E. The lagged correlation suggests that southeast Asian surface temperature anomalies may act as intermediate variables. Copyright

The Relationship between Sea Surface Temperature and Thermocline Depth in the Eastern Equatorial Pacific

The time dependence of the local relation between sea surface temperature (SST) and thermocline depth in the central and eastern equatorial Pacific Ocean is analyzed for the period 1990‐99, using subsurface temperature measurements from the Tropical Atmosphere‐Ocean Array/Triangle Trans-Ocean Buoy Network (TAO/TRITON) buoy array. Thermocline depth anomalies lead SST anomalies in time, with a longitude-dependent delay ranging from 2 weeks in the eastern Pacific to 1 year in the central Pacific. The lagged correlation between thermocline depth and SST is strong, ranging from r . 0.9 in the east to r 0.6 at 1708W. Time-lagged correlations between thermocline depth and subsurface temperature anomalies indicate vertical advection of temperature anomalies from the thermocline to the surface in the eastern Pacific. The measurements are compared with the results of forced OGCM and linear model experiments. Using model results, it is shown that the delay between thermocline depth and SST is caused mainly by upwelling and mixing between 1408 and 908W. Between 1708E and 1408W the delay has a different explanation: thermocline depth anomalies travel to the eastern Pacific, where upwelling creates SST anomalies that in turn cause anomalous wind in the central Pacific. SST is then influenced by these wind anomalies.

Balanced Ocean-Data Assimilation near the Equator

Abstract The question is addressed whether using unbalanced updates in ocean-data assimilation schemes for seasonal forecasting systems can result in a relatively poor simulation of zonal currents. An assimilation scheme, where temperature observations are used for updating only the density field, is compared to a scheme where updates of density field and zonal velocities are related by geostrophic balance. This is done for an equatorial linear shallow-water model. It is found that equatorial zonal velocities can be detoriated if velocity is not updated in the assimilation procedure. Adding balanced updates to the zonal velocity is shown to be a simple remedy for the shallow-water model. Next, optimal interpolation (OI) schemes with balanced updates of the zonal velocity are implemented in two ocean general circulation models. First tests indicate a beneficial impact on equatorial upper-ocean zonal currents.

El Niño and Greenhouse Warming: Results from Ensemble Simulations with the NCAR CCSM

Abstract The changes in model ENSO behavior due to an increase in greenhouse gases, according to the Intergovernmental Panel on Climate Change (IPCC) Business-As-Usual scenario, are investigated using a 62-member ensemble 140-yr simulation (1940–2080) with the National Center for Atmospheric Research Community Climate System Model (CCSM; version 1.4). Although the global mean surface temperature increases by about 1.2 K over the period 2000–80, there are no significant changes in the ENSO period, amplitude, and spatial patterns. To explain this behavior, an analysis of the simulation results is combined with results from intermediate complexity coupled ocean–atmosphere models. It is shown that this version of the CCSM is incapable of simulating a correct meridional extension of the equatorial wind stress response to equatorial SST anomalies. The wind response pattern is too narrow and its strength is insensitive to background SST. This leads to a more stable Pacific climate system, a shorter ENSO period, ...

On the Impact of Local Feedbacks in the Central Pacific on the ENSO Cycle

Abstract While sea surface temperature (SST) anomalies in the eastern equatorial Pacific are dominated by the thermocline feedback, in the central equatorial Pacific local wind effects, such as zonal advection, are important as well. El Nino–Southern Oscillation (ENSO) simulations with a linear model improve markedly if these effects are included as a local wind stress feedback on SST. An atmosphere model that reacts both to eastern and central Pacific SST anomalies is needed for producing a realistic ENSO cycle. First, simulations are studied of a linear 1.5-layer reduced-gravity ocean model and a linear SST anomaly equation, forced by observed monthly wind stress. If only the thermocline feedback is present in the SST equation, SST can be simulated well in the eastern Pacific, but, contrary to observations, central Pacific SST is out of phase with the eastern Pacific. If a wind stress feedback is added in the SST equation, as a term proportional to the zonal wind stress, correlations between observed an...

Tracking Down the ENSO Delayed Oscillator with an Adjoint OGCM

Abstract According to the delayed-oscillator picture of ENSO, a positive SST anomaly in the eastern tropical Pacific will cause westerly wind anomalies closer to the date line to first give a positive feedback, and later, via planetary wave reflection at the western boundary, a negative feedback. The aim of this study is to follow a chain of sensitivities that lead to a delayed-oscillator mechanism in a general circulation model. To this end, the adjoint of such an ocean model is used for studying sensitivities of ENSO indices. The ocean model used in this study is the Hamburg Ocean Primitive Equation (HOPE) ocean general circulation model. Its adjoint has been constructed using the Adjoint Model Compiler. Applied to a scalar function computed with a forward model run, an adjoint run goes back in time and calculates sensitivities as the derivatives of this function to forcing fields or ocean state variables at earlier times. Results from six adjoint runs are reported, tracing the sensitivities of the NINO...

Boundary-Layer Model Results for Wind-Sea Growth

Abstract A numerical model of the boundary layer of the atmosphere above a gravity surface wave is reviewed. The model results are used to obtain an expression for the wind input, the wave growth due to the wind. This is done for wave components that propagate at an arbitrary angle to the wind. Like other purely theoretical expressions for the wind input, the wind input from the boundary-layer model is much smaller than the wind input inferred from field experiments. To study the growth of wind sea, the wind input of the third-generation wave model WAM is replaced by the wind input from the boundary-layer model. The original WAM used a wind input that was inferred from field experiments. For the wave-wave interactions the discrete-interaction approximation is used, while the dissipation is tuned to get an appropriate saturation sea state. The balance between wind input, dissipation, and wave-wave interactions in the energy-containing range of the wave spectrum in this version of the WAM is very different ...

Variational Assimilation of Tropical Atmosphere-Ocean and expendable bathythermograph data in the Hamburg Ocean Primitive Equation ocean general circulation model, adjusting the surface fluxes in the tropical ocean

A four-dimensional variational method has been developed that assimilates expandable bathythermograph and Tropical Atmosphere-Ocean subsurface temperature data into the Hamburg Ocean Primitive Equation model. The method decreases the misfit between model and observed ocean temperatures by adjusting the surface forcing. The main goal of the assimilation scheme is to improve ocean analyses in the tropical Pacific. As a first study, only wind stress is adjusted in the assimilation. In two identical twin experiments it is demonstrated that the scheme works well in the equatorial Pacific. The scheme is capable of reducing errors in the ocean analysis that originate either from the wind stress forcing or the initial state. The impact of model errors on the data assimilation is investigated in a experiment with real observations. In this experiment the temperature innovations near the equator are comparable to those of an optimal interpolation data assimilation scheme.