What controls phase-locking of ENSO to boreal winter in coupled GCMs?

In this study, the phase-locking of El Nino Southern Oscillation (ENSO) in a coupled model with different physical parameter values is investigated. It is found that there is a dramatic change in ENSO phase-locking in response to a slight change in the Tokioka parameter, which is a minimum entrainment rate threshold in the cumulus parameterization. With a smaller Tokioka parameter, the model simulates ENSO peak in the boreal summer season rather than in the winter season as observed. It is revealed that the differences in climatological zonal sea surface temperature (SST) gradient and its associated mean state changes are crucial to determine the phase-locking of ENSO. In the simulations with smaller Tokioka parameter values, climatological zonal SST gradient during the boreal summer is excessively large, because the zonally-asymmetric SST change (i.e., SST increase is relatively smaller over the eastern Pacific) is maximum during the boreal summer when the eastern Pacific SST is the coolest of the year. The enhanced climatological zonal SST gradient in boreal summer reduces the convection over the eastern Pacific, which leads to a weakening of air–sea coupling strength. The minimum coupling strength during summer prevents SST anomalies from further development in the following season, which favors SST maximum during summer. In addition, enhanced zonal SST gradient and resultant thermocline shoaling over the eastern Pacific lead to excessive zonal advective feedback and thermocline feedback. Atmospheric damping is also weakened during boreal summer season. These changes due to feedback processes allow an excessive development of SST anomalies during the summer time, and lead to a summer peak of ENSO. The importance of basic state change for the ENSO phase-locking is also validated in a multi-model framework using the Coupled Model Intercomparison Project phase-3 archive. It is found that several of the climate models have the same problem in producing a summer peak of ENSO. Consistent with the simulations with different physical parameter values, these models have minimum air–sea coupling strength during the boreal summer season. Also, they have stronger climatological zonal SST gradient and shallower climatological thermocline depth over the eastern Pacific during the boreal summer season.     

Tomographic measurements of pore filling at infiltration fronts

For certain porous media and initial conditions, constant flux infiltrations show a saturation profile which exhibits overshoot. This overshoot is the cause of gravity driven fingering, cannot be described by standard models of unsaturated flow, and is likely controlled by the exact nature of the pore filling at the initial front. Here we report synchrotron X-ray micro-tomography measurements of the porous medium and measure which pores are filled by water and air at the initial wetting front as a function of flux. We find that at high fluxes all the pores are filled with water; for intermediate fluxes, the pores along the edge of the column remain unsaturated; and for low fluxes the pores in the bulk of the experimental column remain unsaturated. This suggests that the unsaturated overshoot conditions observed at higher fluxes are primarily an edge effect of the column. The results can help delineate the correct continuum models that can capture overshoot and gravity driven fingering.     

Testing bedload transport formulae using morphologic transport estimates and field data: lower Fraser River,British Columbia

Morphologic transport estimates available for a 65‐km stretch of Fraser River over the period 1952–1999 provide a unique opportunity to evaluate the performance of bedload transport formulae for a large river over decadal time scales. Formulae tested in this paper include the original and rational versions of the Bagnold formula, the Meyer‐Peter and Muller formula and a stream power correlation. The generalized approach adopted herein does not account for spatial variability in flow, bed structure and channel morphology. However, river managers and engineers, as well as those studying rivers within the context of long‐term landscape change, may find this approach satisfactory as it has minimal data requirements and provides a level of process specification that may be commensurable with longer time scales. Hydraulic geometry equations for width and depth are defined using morphologic maps based on aerial photography and bathymetric survey data. Comparison of transport predictions with bedload transport measurements completed at Mission indicates that the original Bagnold formula most closely approximates the main trends in the field data. Sensitivity analyses are conducted to evaluate the impact of inaccuracies in input variables width, depth, slope and grain size on transport predictions. The formulae differ in their sensitivity to input variables and between reaches. Average annual bedload transport predictions for the four formulae show that they vary between each other as well as from the morphologic transport estimates. The original Bagnold and Meyer‐Peter and Muller formulae provide the best transport predictions, although the former underestimates while the latter overestimates transport rates. Based on our findings, an error margin of up to an order of magnitude can be expected when adopting generalized approaches for the prediction of bedload transport. Copyright © 2005 John Wiley & Sons, Ltd.     

Changes in El Niño and La Niña teleconnections over North Pacific–America in the global warming simulations

The change in the teleconnections of both El Niño and La Niña over the North Pacific and American regions due to a future greenhouse warming has been analyzed herein by means of diagnostics of the Intergovernmental Panel on Climate Change-Fourth Assessment Report (IPCC-AR4) coupled general circulation models (CGCMs). Among the IPCC-AR4 CGCM simulations, the composites of the eight-member multimodel ensemble are analyzed. In most CGCMs, the tropical Pacific warming due to the increase of CO₂ concentration in the atmosphere promotes the main convection centers in the equatorial Pacific associated with both El Niño and La Niña to the east. The eastward shift of the convection center causes a systematic eastward shift of not only El Niño but also La Niña teleconnection patterns over the North Pacific and America, which is demonstrated in the composite maps of 500 hPa circulation, surface temperature, and the precipitation against El Niño and La Niña, as observed in a comparison between the pre-industrial and CO₂ doubling experiments. Thus, a systematic eastward migration of convection centers in the tropical Pacific associated with both El Niño and La Niña due to a future global warming commonly causes the eastward shift of the atmospheric teleconnection patterns over the Northern Hemisphere.     

Improvement of seasonal forecasts with inclusion of tropical instability waves on initial conditions

Positive impacts of tropical instability waves (TIWs) in initial conditions on seasonal forecasts are investigated using a air-sea coupled GCM. Due to coarse observational networks and deficiencies in widely-used initialization methods (e.g. 3DVAR or OI methods), TIW variability in oceanic initial conditions is excessively suppressed. It ruins the interaction between TIWs and climate states, therefore, degrades the climate forecast skills. To settle this problem, TIW patterns obtained from free integration is added to the spatially-smoothed initial conditions to simulate realistic seasonal TIW variability (TIWV). Through 20-year ensemble forecast experiments, it is shown that seasonal TIWV with TIWs-seeded initial conditions is significantly stronger until 2-month lead time. In addition, enhanced TIWV amplifies nonlinear relationship between TIWs and ENSO, which leads realistic simulation of the El Ni?o-La Ni?a asymmetry. As a result of better ENSO simulation, correlation improvement of simulated NINO3 index with TIWs-seeded initial conditions is over 0.1 at 4-month lead time.     

A study on air–sea interaction on the simulated seasonal climate in an ocean–atmosphere coupled model

This study investigates the effects of air–sea interaction upon simulated tropical climatology, focusing on the boreal summer mean precipitation and the embedded intra-seasonal oscillation (ISO) signal. Both the daily coupling of ocean–atmosphere and the diurnal variation of sea surface temperature (SST) at every time step by accounting for the ocean mixed layer and surface-energy budget at the ocean surface are considered. The ocean–atmosphere coupled model component of the global/regional integrated model system has been utilized. Results from the coupled model show better precipitation climatology than those from the atmosphere-only model, through the inclusion of SST–cloudiness–precipitation feedback in the coupled system. Cooling the ocean surface in the coupled model is mainly responsible for the improved precipitation climatology, whereas neither the coupling itself nor the diurnal variation in the SST influences the simulated climatology. However, the inclusion of the diurnal cycle in the SST shows a distinct improvement of the simulated ISO signal, by either decreasing or increasing the magnitude of spectral powers, as compared to the simulation results that exclude the diurnal variation of the SST in coupled models.     

A new measure for assessing the efficiency of hydrological data-driven forecasting models

Abstract

There is a lack of consistency and generality in assessing the performance of hydrological data-driven forecasting models, and this paper presents a new measure for evaluating that performance. Despite the fact that the objectives of hydrological data-driven forecasting models differ from those of the conventional hydrological simulation models, criteria designed to evaluate the latter models have been used until now to assess the performance of the former. Thus, the objectives of this paper are, firstly, to examine the limitations in applying conventional methods for evaluating the data-driven forecasting model performance, and, secondly, to present new performance evaluation methods that can be used to evaluate hydrological data-driven forecasting models with consistency and objectivity. The relative correlation coefficient (RCC) is used to estimate the forecasting efficiency relative to the naïve model (unchanged situation) in data-driven forecasting. A case study with 12 artificial data sets was performed to assess the evaluation measures of Persistence Index (PI), Nash-Sutcliffe coefficient of efficiency (NSC) and RCC. In particular, for six of the data sets with strong persistence and autocorrelation coefficients of 0.966–0.713 at correlation coefficients of 0.977–0.989, the PIs varied markedly from 0.368 to 0.930 and the NSCs were almost constant in the range 0.943–0.972, irrespective of the autocorrelation coefficients and correlation coefficients. However, the RCCs represented an increase of forecasting efficiency from 2.1% to 37.8% according to the persistence. The study results show that RCC is more useful than conventional evaluation methods as the latter do not provide a metric rating of model improvement relative to naïve models in data-driven forecasting.

Editor D. Koutsoyiannis, Associate editor D. Yang

Citation Hwang, S.H., Ham, D.H., and Kim, J.H., 2012. A new measure for assessing the efficiency of hydrological data-driven forecasting models. Hydrological Sciences Journal, 57 (7), 1257–1274.