Diagnosing GCM errors over West Africa using relaxation experiments. Part I: summer monsoon climatology and interannual variability

The CNRM atmospheric general circulation model Arpege-Climat is relaxed towards atmospheric reanalyses outside the 10°S?C32°N 30°W?C50°E domain in order to disentangle the regional versus large-scale sources of climatological biases and interannual variability of the West African monsoon (WAM). On the one hand, the main climatological features of the monsoon, including the spatial distribution of summer precipitation, are only weakly improved by the nudging, thereby suggesting the regional origin of the Arpege-Climat biases. On the other hand, the nudging technique is relatively efficient to control the interannual variability of the WAM dynamics, though the impact on rainfall variability is less clear. Additional sensitivity experiments focusing on the strong 1994 summer monsoon suggest that the weak sensitivity of the model biases is not an artifact of the nudging design, but the evidence that regional physical processes are the main limiting factors for a realistic simulation of monsoon circulation and precipitation in the Arpege-Climat model. Sensitivity experiments to soil moisture boundary conditions are also conducted and highlight the relevance of land?Catmosphere coupling for the amplification of precipitation biases. Nevertheless, the land surface hydrology is not the main explanation for the model errors that are rather due to deficiencies in the atmospheric physics. The intraseasonal timescale and the model internal variability are discussed in a companion paper.     

ENSO in a hybrid coupled model. Part I: sensitivity to physical parametrizations

 A hybrid coupled model (HCM) for the tropical Pacific ocean-atmosphere system is used to test the effects of physical parametrizations on ENSO simulation. The HCM consists of the Geophysical Fluid Dynamics Laboratory ocean general circulation model coupled to an empirical atmospheric model based on the covariance matrix of observed SST and wind stress anomaly fields. In this two-part work, part I describes the effects of ocean vertical mixing schemes and atmospheric spin-up time on ENSO period. Part II addresses ENSO prediction using the HCM and examines the impact of initialization schemes. The standard version of the HCM exhibits spatial and temporal evolution that compare well to observations, with irregular cycles that tend to exhibit 3- and 4-year frequency-locking behavior. Effects in the vertical mixing parametrization that produce stronger mixing in the surface layer give a longer inherent ENSO period, suggesting model treatment of vertical mixing is crucial to the ENSO problem. Although the atmospheric spin-up time scale is short compared to ENSO time scales, it also has a significant effect in lengthening the ENSO period. This suggests that atmospheric time scales may not be truly negligible in quantitative ENSO theory. Overall, the form and evolution mechanism of the ENSO cycle is robust, even though the period is affected by these physical parametrizations. Received: 17 April 1998 / Accepted: 22 July 1999     

Northern Hemisphere midlatitude cyclone variability in GCM simulations with different ocean representations

The impact of different ocean models or sea surface temperature (SST) and sea-ice concentrations on cyclone tracks in the Northern Hemisphere midlatitudes is determined within a hierarchy of model simulations. A reference simulation with the coupled atmosphere ocean circulation model ECHAM/HOPE is compared with simulations using ECHAM and three simplified ocean and sea-ice representations: (1) a variable depth mixed layer (ML) ocean, (2) forcing by varying SST and sea-ice, and (3) with climatological SST and sea-ice; the latter two are from the coupled ECHAM/HOPE integration. The reference simulation reproduces the observed cyclone tracks. The cyclones are tracked automatically by a standard routine and the variability of individual cyclone trajectories within the storm tracks is determined by a cluster approach. In the forced simulation with varying SST, the geographical distribution and the statistics of the cyclones are not altered compared to the coupled reference simulation. In the ML- and the climatological simulation, deviations of the mean cyclone distribution are found which occur mainly in the North Pacific, and can partially be traced back to missing El Niño/Southern Oscillation (ENSO) variability. The climatological experiment is superior to the ML-experiment. The variability of the individual cyclone trajectories, as determined by the cluster analysis, reveals the same types and frequencies of propagation directions for all four representations of the lower boundary. The largest discrepancies for the cluster occupations are found for the climatological and the ML-simulation.     

Diagnosing GCM errors over West Africa using relaxation experiments. Part II: intraseasonal variability and African easterly waves

A near-global grid-point nudging of the Arpege-Climat atmospheric General Circulation Model towards ECMWF reanalyses is used to diagnose the regional versus remote origin of the summer model biases and variability over West Africa. First part of this study revealed a limited impact on the monsoon climatology compared to a control experiment without nudging, but a significant improvement of interannual variability, although the amplitude of the seasonal anomalies remained underestimated. Focus is given here on intraseasonal variability of monsoon rainfall and dynamics. The reproducible part of these signals is investigated through 30-member ensemble experiments computed for the 1994 rainy season, a year abnormally wet over the Sahel but representative of the model systematic biases. In the control experiment, Arpege-Climat simulates too few rainy days that are associated with too low rainfall amounts over the central and western Sahel, in line with the seasonal dry biases. Nudging the model outside Africa tends to slightly increase the number of rainy days over the Sahel, but has little effect on associated rainfall amounts. However, results do indicate that a significant part of the monsoon intraseasonal variability simulated by Arpege-Climat is controlled by lateral boundary conditions. Parts of the wet/dry spells over the Sahel occur in phase in the 30 members of the nudging experiment, and are therefore embedded in larger-scale variability patterns. Inter-member spread is however not constant across the selected summer season. It is partly controlled by African Easterly Waves, which show dissimilar amplitude from one member to another, but a coherent phasing in all members. A lowpass filtering of the nudging fields suggests that low frequency variations in the lateral boundary conditions can lead to eastward extensions of the African Easterly Jet, creating a favorable environment for easterly waves, while high frequency perturbations seem to control their phasing.     

Vegetation and climate variability: a GCM modelling study

Vegetation is known to interact with the other components of the climate system over a wide range of timescales. Some of these interactions are now being taken into account in models for climate prediction. This study is an attempt to describe and quantify the climate–vegetation coupling at the interannual timescale, simulated with a General Circulation Model (HadSM3) coupled to a dynamic global vegetation model (TRIFFID). Vegetation variability is generally strongest in semi-arid areas, where it is driven by precipitation variability. The impact of vegetation variability on climate is analysed by using multivariate regressions of boundary layer fluxes and properties, with respect to soil moisture and vegetation fraction. Dynamic vegetation is found to significantly increase the variance in the surface sensible and latent heat fluxes. Vegetation growth always causes evapotranspiration to increase, but its impact on sensible heat is less straightforward. The feedback of vegetation on sensible heat is positive in Australia, but negative in the Sahel and in India. The sign of the feedback depends on the competing influences, at the gridpoint scale, of the turbulent heat exchange coefficient and the surface (stomatal) water conductance, which both increase with vegetation growth. The impact of vegetation variability on boundary layer potential temperature and relative humidity are shown to be small, implying that precipitation persistence is not strongly modified by vegetation dynamics in this model. We discuss how these model results may improve our knowledge of vegetation–atmosphere interactions and help us to target future model developments.     

Assessment of surface drag coefficient parametrizations based on observations and simulations using the Weather Research and Forecasting model

海气界面动量交换对台风发展起着重要作用,其估算公式依赖于拖曳系数。本文利用观测和台风模拟试验对八种拖曳系数参数化方案进行系统的评估。结果表明,相对于早期的参数化方案,近些年提出的参数化方案对拖曳系数的描述有了显著的改进,主要体现在高风速条件下。不同的拖曳系数参数化方案对超强台风"海燕"的模拟路径几乎没有影响,但是对其强度、尺寸和结构的模拟结果有显著影响。     

Interannual variability and predictability in an ensemble of AMIP climate simulations conducted with the CCC GCM2

This study considers an ensemble of six 10-year climate simulations conducted with the Canadian Climate Centre 2nd generation General Circulation Model (CCC GCM2). Each simulation was forced according to the Atmospheric Model Intercomparison Project (AMIP) experimental protocol using monthly mean sea surface temperatures and sea-ice extents based on observations for January, 1979 to December 1988. One simulation, conducted on a CRAY computer, was initiated from analysed 1 January 1979 conditions while the remaining 5 simulations, conducted on a NEC computer, were initiated from previously simulated model states obtained from a long control integration. The interannual variability and potential predictability of simulated and observed 500 hPa geopotential, 850 hPa temperature and 300 hPa stream function are examined and inter-compared using statistical analysis of variance techniques to partition variance into a number of components. The boundary conditions specified by AMIP are found to induce statistically significant amounts of predictable variance on the interannual time scale in the tropics and, to a lesser extent, at extratropical latitudes. In addition, local interactions between the atmosphere and the land surface apparently induce significant amounts of potentially predictable interannual variance in the tropical lower atmosphere and also at some locations in the temperate lower atmosphere. No evidence was found that the atmosphere's internal dynamics on their own generate potentially predictable variations on the interannual time scale. The sensitivity of the statistical methods used is demonstrated by the fact that we are able to detect differences between the climates simulated on the two computers used. The causes of these physically insignificant changes are traced. The statistical procedures are checked by confirming that the choice of initial conditions does not lead to significant inter-simulation variation. The simulations are also interpreted as an ensemble of climate forecasts that rely only on the specified boundary conditions for their predictive skill. The forecasts are verified against observations and against themselves. In agreement with other studies it was found that the forecasts have very high skill in the tropics and moderate skill in the extratropics. Received: 18 December 1995 / Accepted: 4 April 1996     

The impact of new physical parametrizations in the Hadley Centre climate model: HadAM3

 Results are presented from the latest version of the Hadley Centre climate model, HadAM3 (Hadley Centre Atmospheric Model version 3). It represents a significant improvement over the previous version, HadAM2b. This is demonstrated using a series of ten year integrations with AMIP (Atmospheric Model Intercomparison Project) boundary conditions. The work covers three aspects of model performance: (1) it shows the improvements in the mean climate in changing from HadAM2b to HadAM3; (2) it demonstrates that the model now compares well with observations and (3) it isolates the impacts of new physical parametrizations. Received: 17 August 1998 / Accepted: 20 July 1999     

La Plata basin precipitation variability in spring: role of remote SST forcing as simulated by GCM experiments

An ensemble of nine experiments with the same interannually varying sea surface temperature (SST), as boundary forcing, and different initial conditions is used to investigate the role of tropical oceans in modulating precipitation variability in the region of La Plata Basin (LPB). The results from the ensemble are compared with a twentieth-century experiment performed with a coupled ocean-atmosphere model, sharing the same atmospheric component. A rotated empirical orthogonal functions analysis of South America precipitation shows that the dominant mode of variability in spring is realistically captured in both experiments. Its principal component (RPC1) correlated with global SST and atmospheric fields identifies the pattern related to El Niño Southern Oscillation and its large-scale teleconnections. Overall the pattern is well simulated in the tropical southern Pacific Ocean, mainly in the ensemble, but it is absent or too weak in other oceanic areas. The coupled model experiment shows a more realistic correlation in the subtropical South Atlantic where air-sea interactions contribute to the relationship between LPB precipitation and SST. The correspondence between model and data is much improved when the composite analysis of SST and atmospheric fields is done over the ensemble members having an RPC1 in agreement with the observations: the improvement relies on avoiding climate noise by averaging only over members that are statistically similar. Furthermore, the result suggests the presence of a high level of uncertainty due to internal atmospheric variability. The analysis of some individual years selected from the model and data RPC1 comparison reveals interesting differences among rainy springs in LPB. For example, 1982, which corresponds to a strong El Niño year, represents a clean case with a distinct wave train propagating from the central Pacific and merging with another one from the eastern tropical south Indian Ocean. The year 2003 is an example of a rainy spring in LPB not directly driven by remote SST forcing. In this case the internal variability has a dominant role, as the model is not able to reproduce the correct local precipitation pattern.     

Climate variability in the south-eastern tropical Pacific and its relation with ENSO: a GCM study

About a third of the El-Niño/Southern Oscillation (ENSO) variability in the HadCM3 coupled general-circulation model is shown to be associated with variability in the south-east tropical Pacific (SETP) area. Sea-surface temperature (SST) anomalies along the east Pacific tend to precede ENSO anomalies. In HadCM3, SST tendencies in the SETP area are controlled mainly by surface latent heat fluxes and short-wave cloud forcing. Interannual SST anomalies in the SETP tend to propagate meridionally. In the winter season (JJA), this is consistent with a wind-evaporation-SST (WES) mode. Coupling with the strato-cumulus cloud (Sc) cover is critical in reducing the evaporative damping of the WES mode, and external forcing is provided by extratropical circulation anomalies. In spring, SETP variability and ENSO are coupled via the low-level circulation, resulting in a mutual reinforcement. Cloud-cover anomalies are not strongly controlled by local SSTs, and appear mainly dependent on atmospheric meridional advection. The apparent association between cold SSTs and Sc cover does not reflect a positive local feedback. These conclusions are not sensitive to the model’s warm SST bias, associated with reduced stratocumulus clouds and weak southerly wind stress, which depends on erroneous near-field orographic forcing of the coastal circulation. Some of our results are supported by similar evidence from observational datasets and other CMIP3 models.     

ENSO variability and atmospheric response in a global coupled atmosphere-ocean GCM

The interannual variability associated with the El Ni?o/Southern Oscillation (ENSO) cycle is investigated using a relatively high-resolution (T42) coupled general circulation model (CGCM) of the atmosphere and ocean. Although the flux correction is restricted to annual means of heat and freshwater, the annual as well as the seasonal climate of the CGCM is in good agreement with that of the atmospheric model component forced with observed sea surface temperatures (SSTs). During a 100-year simulation of the present-day climate, the model is able to capture many features of the observed interannual SST variability in the tropical Pacific. This includes amplitude, lifetime and frequency of occurrence of El Ni?o events and also the phase locking of the SST anomalies to the annual cycle. Although the SST warming during the evolution of El Ni?os is too confined spatially, and the warming along the Peruvian coast is much too weak, the patterns and magnitudes of key atmospheric anomalies such as westerly wind stress and precipitation, and also their eastward migration from the western to the central equatorial Pacific is in accord with observations. There is also a qualitative agreement with the results obtained from the atmospheric model forced with observed SSTs from 1979 through 1994. The large-scale dynamic response during the mature phase of ENSO (December through February) is characterized by an eastward displacement and weakening of the Walker cell in the Pacific while the Hadley cell intensifies and moves equatorward. Similar to the observations, there is a positive correlation between tropical Pacific SST and the winter circulation in the North Pacific. The deepening of the Aleutian low during the ENSO winters is well captured by the model as well as the cooling in the central North Pacific and the warming over Canada and Alaska. However, there are indications that the anomalies of both SST and atmospheric circulation are overemphasized in the North Pacific. Finally, there is evidence of a coherent downstream effect over the North Atlantic as indicated by negative correlations between the PNA index and the NAO index, for example. The weakening of the westerlies across the North Atlantic in ENSO winters which is related to a weakening and southwestward displacement of the Icelandic low, is in broad agreement with the observations, as well as the weak tendency for colder than normal winters in Europe. Received: 31 October 1995 / Accepted: 29 May 1996     

Interannual variability and predictability of African easterly waves in a GCM

The interannual variability of African Easterly Waves (AEWs) is assessed with the help of spatio-temporal spectral analysis (STSA) and complex empirical orthogonal functions methods applied to the results of ten-member multiyear ensemble simulations. Two sets of experiments were conducted with the Météo-France ARPEGE-Climat GCM, one with interactive soil moisture (control), and the other with soil moisture relaxed towards climatological monthly means calculated from the control. Composites of Soudano–Sahelian AEWs were constructed and associated physical processes and dynamics were studied in the frame of the waves. It is shown that the model is able to simulate realistically some interannual variability in the AEWs, and that this dynamical aspect of the West African climate is potentially predictable (i.e. signal can be extracted from boundary conditions relatively to internal error of the GCM), especially along the moist Guinean coast. Compared with ECMWF 15-year reanalysis (ERA15), the maximum activity of AEWs is located too far to the South and is somewhat too zonal, but the main characteristics of the waves are well represented. The major impact of soil moisture relaxation in the GCM experiments is to reduce the seasonal potential predictability of AEWs over land by enhancing their internal variability.     

Surface energy balance complexity in GCM land surface models. Part II: coupled simulations

 Global coupled simulations with the Bureau of Meteorology Research Centre climate model and the CHAmeleon Surface Model (CHASM) are used to examine how four general extensions to the representation of the basic land surface energy balance affect simulated land-atmosphere interface variables: evaporation, precipitation, skin temperature and air temperature. The impacts of including separate surface energy balance calculations for: vegetated and non-vegetated portions of the land surface; an explicit parametrisation of canopy resistance; explicit bare ground evaporation; and explicit canopy interception are isolated and quantified. The hypothesis that these aspects of surface energy balance parametrisation do not contain substantial information at the monthly time scale (and are therefore not important to consider in a land surface model) is shown to be false. Considerable sensitivity to each of the four general surface energy balance extensions is identified in average pointwise monthly changes for important land-atmosphere interface variables. Average pointwise changes in monthly precipitation and land evaporation are equal to about 40 and 31–37% of the global-average precipitation and land evaporation respectively. Average pointwise changes for land surface skin temperature and lowest model layer air temperature are about 2 and 0.9 K respectively. The average pointwise change and average pointwise biases are statistically significant at 95% in all cases. Substantial changes to zonally average variables are also identified. We demonstrate how the globally averaged surface resistance parameter can vary from 150 to 25 s/m depending on which aspects of the surface energy balance are treated implicitly. We also show that if interception is treated implicitly, the effective surface resistance must vary geographically in order to capture the behaviour of a model which treats this process explicitly. The implication of these results for the design of land surface models is discussed. Received: 8 July 1999 / Accepted: 1 September 2000     

An ocean wind-wave climatology for the Southern Brazilian Shelf. Part I: Problem presentation and model validation

Geomorphological features and sparse visual wave measurements, presented in previous works, point out to the possible existence of alongshore wave energy gradients over the Southern Brazilian Shelf (SBS). After describing the two numerical models utilized and the model grids and settings, the present study evaluated the proposed validation of the basin-scale results against orbital altimetry and the regional-scale results against the two available wave-buoy data, discussing the extent to which the model reproduced local reality. The basin-scale model results of significant wave height could be considered as in good agreement with observations, presenting remarkable similarities with observed altimetry. Regarding the regional-scale modeling, both significant wave height and peak wave periods were considered as in good agreement with observations. The peak wave directions, however, were classified as in poor agreement, once the ESE waves were erroneously reproduced as E. Increased spatial resolution certainly played a role, but it was the lowering of bottom friction that represented the major improvement in the coastal grid simulations.     

An annual cycle of vegetation in a GCM. Part I: implementation and impact on evaporation

The sensitivity of evaporation to a prescribed vegetation annual cycle is examined globally in the Met Office Hadley Centre Unified Model (HadAM3) which incorporates the Met Office Surface Exchange Scheme (MOSES2) as the land surface scheme. A vegetation annual cycle for each plant functional type in each grid box is derived based on satellite estimates of Leaf Area Index (LAI) obtained from the nine-year International Satellite Land Surface Climatology Project II dataset. The prescribed model vegetation seasonality consists of annual cycles of a number of structural vegetation characteristics including LAI as well as canopy height, surface roughness, canopy water capacity, and canopy heat capacity, which themselves are based on empirical relationships with LAI. An annual cycle of surface albedo, which in the model is a function of soil albedo, surface soil moisture, and LAI, is also modelled and agrees reasonably with observed estimates of the surface albedo annual cycle. Two 25-year numerical experiments are completed and compared: the first with vegetation characteristics held at annual mean values, the second with prescribed realistic seasonally varying vegetation. Initial analysis uncovered an unrealistically weak relationship between evaporation and vegetation state that is primarily due to the insensitivity of evapotranspiration to LAI. This weak relationship is strengthened by the adjustment of two MOSES2 parameters that together improve the models LAI-surface conductance relationship by comparison with observed and theoretical estimates. The extinction coefficient for photosynthetically active radiation, k _par , is adjusted downwards from 0.5 to 0.3, thereby enhancing the LAI-canopy conductance relationship. A canopy shading extinction coefficient, k _sh , that controls what fraction of the soil surface beneath a canopy is directly exposed to the overlying atmosphere is increased from 0.5 to 1.0, which effectively reduces soil evaporation under a dense canopy. When the experiments are repeated with the adjusted parameters, the relationship between evaporation and vegetation state is strengthened and is more spatially consistent. At nearly all locations, the annual cycle of evaporation is enhanced in the seasonally varying vegetation experiment. Evaporation is stronger during the peak of the growing season and, in the tropics, reduced transpiration during the dry season when LAI is small leads to significantly lower total evaporation.     

Quantifying uncertainty in changes in extreme event frequency in response to doubled CO2 using a large ensemble of GCM simulations

We discuss equilibrium changes in daily extreme surface air temperature and precipitation events in response to doubled atmospheric CO₂, simulated in an ensemble of 53 versions of HadSM3, consisting of the HadAM3 atmospheric general circulation model (GCM) coupled to a mixed layer ocean. By virtue of its size and design, the ensemble, which samples uncertainty arising from the parameterisation of atmospheric physical processes and the effects of natural variability, provides a first opportunity to quantify the robustness of predictions of changes in extremes obtained from GCM simulations. Changes in extremes are quantified by calculating the frequency of exceedance of a fixed threshold in the 2 × CO₂ simulation relative to the 1 × CO₂ simulation. The ensemble-mean value of this relative frequency provides a best estimate of the expected change while the range of values across the ensemble provides a measure of the associated uncertainty. For example, when the extreme threshold is defined as the 99th percentile of the 1 × CO₂ distribution, the global-mean ensemble-mean relative frequency of extremely warm days is found to be 20 in January, and 28 in July, implying that events occurring on one day per hundred under present day conditions would typically occur on 20–30 days per hundred under 2 × CO₂ conditons. However the ensemble range in the relative frequency is of similar magnitude to the ensemble-mean value, indicating considerable uncertainty in the magnitude of the increase. The relative frequencies in response to doubled CO₂ become smaller as the threshold used to define the extreme event is reduced. For one variable (July maximum daily temperature) we investigate this simulated variation with threshold, showing that it can be quite well reproduced by assuming the response to doubling CO₂ to be characterised simply as a uniform shift of a Gaussian distribution. Nevertheless, doubling CO₂ does lead to changes in the shape of the daily distributions for both temperature and precipitation, but the effect of these changes on the relative frequency of extreme events is generally larger for precipitation. For example, around one-fifth of the globe exhibits ensemble-mean decreases in time-averaged precipitation accompanied by increases in the frequency of extremely wet days. The ensemble range of changes in precipitation extremes (relative to the ensemble mean of the changes) is typically larger than for temperature extremes, indicating greater uncertainty in the precipitation changes. In the global average, extremely wet days are predicted to become twice as common under 2 × CO₂ conditions. We also consider changes in extreme seasons, finding that simulated increases in the frequency of extremely warm or wet seasons under 2 × CO₂ are almost everywhere greater than the corresponding increase in daily extremes. The smaller increases in the frequency of daily extremes is explained by the influence of day-to-day weather variability which inflates the variance of daily distributions compared to their seasonal counterparts.     

Contrasting Indian Ocean SST variability with and without ENSO influence: A coupled atmosphere-ocean GCM study

Summary In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO’s influence on the interannual sea-surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSO’s influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3–5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin-wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east–west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.