Mechanisms for projected future changes in south Asian monsoon precipitation

Results are first presented from an analysis of a global coupled climate model regarding changes in future mean and variability of south Asian monsoon precipitation due to increased atmospheric CO₂ for doubled (2 × CO₂) and quadrupled (4 × CO₂) present-day amounts. Results from the coupled model show that, in agreement with previous studies, mean area-averaged south Asian monsoon precipitation increases with greater CO₂ concentrations, as does the interannual variability. Mechanisms producing these changes are then examined in a series of AMIP2-style sensitivity experiments using the atmospheric model (taken from the coupled model) run with specified SSTs. Three sets of ensemble experiments are run with SST anomalies superimposed on the AMIP2 SSTs from 1979–97: (1) anomalously warm Indian Ocean SSTs, (2) anomalously warm Pacific Ocean SSTs, and (3) anomalously warm Indian and Pacific Ocean SSTs. Results from these experiments show that the greater mean monsoon precipitation is due to increased moisture source from the warmer Indian Ocean. Increased south Asian monsoon interannual variability is primarily due to warmer Pacific Ocean SSTs with enhanced evaporation variability, with the warmer Indian Ocean SSTs a contributing but secondary factor. That is, for a given interannual tropical Pacific SST fluctuation with warmer mean SSTs in the future climate, there is enhanced evaporation and precipitation variability that is communicated via the Walker Circulation in the atmosphere to the south Asian monsoon to increase interannual precipitation variability there. This enhanced monsoon variability occurs even with no change in interannual SST variability in the tropical Pacific.     

Potential future changes in the Indian summer monsoon due to greenhouse warming: analysis of mechanisms in a global time-slice experiment

In this study the potential impact of the anticipated increase in the greenhouse gas concentrations on different aspects of the Indian summer monsoon is investigated, focusing on the role of the mechanisms leading to these changes. Both changes in the mean aspects of the Indian summer monsoon and changes in its interannual variability are considered. This is done on the basis of a global time-slice experiment being performed with the ECHAM4 AGCM at a high horizontal resolution of T106. The experiment consists of two 30-year simulations, one representing the present-day climate (period: 1970–1999) and one representing the future climate (period: 2060–2089). The time-slice experiment predicts an intensification of the mean rainfall associated with the Indian summer monsoon due to the general warming, while the future changes in the large-scale flow indicate a weakening of the monsoon circulation in the upper troposphere and only little change in the lower troposphere. The intensification of the monsoon rainfall in the Indian region is related to an intensification of the atmospheric moisture transport into this region. The weakening of the monsoon flow is caused by a pronounced warming of the sea surface temperatures in the central and eastern tropical Pacific and the associated alterations of the Walker circulation. A future increase of the temperature difference between the Indian Ocean and central India as well as a future reduction of the Eurasian snow cover in spring would, by themselves, lead to a strengthening of the monsoon flow in the future. These two mechanisms compensate for the weakening of the low-level monsoon flow induced by the warming of the tropical Pacific. The time-slice experiment also predicts a future increase of the interannual variability of both the rainfall associated with the Indian summer monsoon and of the large-scale flow. A major part of this increase is accounted for by enhanced interannual variability of the sea surface temperatures in the central and eastern tropical Pacific.     

The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius–Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that such effects are small compared to other sources of uncertainty, although models with large Arabian Sea cold SST biases may suppress the range of potential outcomes for changes to future early monsoon rainfall.     

热带印度洋春季海表温度异常与南海夏季风强度变化的关系

利用50年的Reynolds月平均海表温度资料和NCEP/NCAR全球大气再分析资料,分析了热带印度洋春季海温异常对南海夏季风强度变化的影响。结果表明:1)热带印度洋春季海表温度距平(SSTA)的模态主要是全区一致型(USBM)和热带南印度洋偶极型(SIODM),USBM模态既有年际时间尺度的变化特征,又有年际以上时间尺度的变化特征,既包含有对冬季ENSO信号响应的变化特征,又有独立于ENSO的变化特征;SIODM模态主要表现为独立于ENSO的年际时间尺度变化。2)USBM模态与南海夏季风强度变化呈显著负相关关系,且二者都是对冬季ENSO信号的响应,USBM模态的年际变化不能独立于ENSO信号影响南海夏季风的强度变化。3)经(1~8年)带通滤波及去除ENSO信号的热带印度洋春季SSTA的SIODM型分布是影响南海夏季风强度变化的主要模态,表现为热带东南印度洋为负(正)、其他海区为正(负)时,南海夏季风强度增强(减弱),大气环流对热带东南印度洋SSTA热力作用的响应是造成这一关系的直接原因,SIODM型的SSTA分布与南海夏季风年际异常关系在热带印度洋长期变化趋势的暖位相期显著,在长期变化趋势的冷位相期不显著。     

A multi-model analysis of the role of the ocean on the African and Indian monsoon during the mid-Holocene

We investigate the role of the ocean feedback on the climate in response to insolation forcing during the mid-Holocene (6,000 year BP) using results from seven coupled ocean–atmosphere general circulation models. We examine how the dipole in late summer sea-surface temperature (SST) anomalies in the tropical Atlantic increases the length of the African monsoon, how this dipole structure is created and maintained, and how the late summer SST warming in the northwest Indian Ocean affects the monsoon retreat in this sector. Similar mechanisms are found in all of the models, including a strong wind evaporation feedback and changes in the mixed layer depth that enhance the insolation forcing, as well as increased Ekman transport in the Atlantic that sharpens the Atlantic dipole pattern. We also consider changes in interannual variability over West Africa and the Indian Ocean. The teleconnection between variations in SST and Sahelian precipitation favor a larger impact of the Atlantic dipole mode in this region. In the Indian Ocean, the strengthening of the Indian dipole structure in autumn has a damping effect on the Indian dipole mode at the interannual time scale.     

Roles of Indian and Pacific Ocean air–sea coupling in tropical atmospheric variability

Sea surface temperature (SST) variations include negative feedbacks from the atmosphere, whereas SST anomalies are specified in stand-alone atmospheric general circulation simulations. Is the SST forced response the same as the coupled response? In this study, the importance of air–sea coupling in the Indian and Pacific Oceans for tropical atmospheric variability is investigated through numerical experiments with a coupled atmosphere-ocean general circulation model. The local and remote impacts of the Indian and Pacific Ocean coupling are obtained by comparing a coupled simulation with an experiment in which the SST forcing from the coupled simulation is specified in either the Indian or the Pacific Ocean. It is found that the Indian Ocean coupling is critical for atmospheric variability over the Pacific Ocean. Without the Indian Ocean coupling, the rainfall and SST variations are completely different throughout most of the Pacific Ocean basin. Without the Pacific Ocean coupling, part of the rainfall and SST variations in the Indian Ocean are reproduced in the forced run. In regions of large mean rainfall where the atmospheric negative feedback is strong, such as the North Indian Ocean and the western North Pacific in boreal summer, the atmospheric variability is significantly enhanced when air–sea coupling is replaced by specified SST forcing. This enhancement is due to the lack of the negative feedback in the forced SST simulation. In these regions, erroneous atmospheric anomalies could be induced by specified SST anomalies derived from the coupled model. The ENSO variability is reduced by about 20% when the Indian Ocean air–sea coupling is replaced by specified SST forcing. This change is attributed to the interfering roles of the Indian Ocean SST and Indian monsoon in western and central equatorial Pacific surface wind variations.     

Pre-onset land surface processes and ��internal�� interannual variabilities of the Indian summer monsoon

It is proposed that, land?Catmosphere interaction around the time of monsoon onset could modulate the first episode of climatological intraseasonal oscillation (CISO) and may generate significant ??internal?? interannual variation in the Indian summer monsoon rainfall. The regional climate model RegCM3 is used over Indian monsoon domain for 27?years of control simulation. In order to prove the hypothesis, another two sets of experiment are performed using two different boundary conditions (El Ni?o year and non-ENSO year). In each of these experiments, a single year of boundary conditions are used repeatedly year after year to generate ??internal?? interannual monsoon variability. Simulation of monsoon climate in the control model run is found to be in reasonably good agreement with observation. However, large rainfall bias is seen over Arabian Sea and Bay of Bengal. The interannual monsoon rainfall variability are of the same order in two experiments, which suggest that the external influences may not be important on the generation of ??internal?? monsoon rainfall variability. It is shown that, a dry (wet) pre-onset land-surface condition increases (decreases) rainfall in June which in turn leads to an anomalous increase (decrease) in seasonal (JJAS) rainfall. The phase and amplitude of CISO are modulated during May?CJune and beyond that the modulation of CISO is quite negligible. Though the pre-onset rainfall is unpredictable, significant modulation of the post-onset monsoon rainfall by it can be exploited to improve predictive skill within the monsoon season.     

Performance of GCMs for seasonal prediction over India��a case study for 2009 monsoon

The 2009 drought in India was one of the major droughts that the country faced in the last 100?years. This study describes the anomalous features of 2009 summer monsoon and examines real-time seasonal predictions made using six general circulation models (GCMs). El Ni?o conditions evolved in the Pacific Ocean, and sea surface temperatures (SSTs) over the Indian Ocean were warmer than normal during monsoon 2009. The observed circulation patterns indicate a weaker monsoon in that year over India with weaker than normal convection over the Bay of Bengal and Indian landmass. Skill of the GCMs during hindcast period shows that neither these models simulate the observed interannual variability nor their multi-model ensemble (MME) significantly improves the skill of monsoon rainfall predictions. Except for one model used in this study, the real-time predictions with longer lead (2- and 1-month lead) made for the 2009 monsoon season did not provide any indication of a highly anomalous monsoon. However, with less lead time (zero lead), most of the models as well as the MME had provided predictions of below normal rainfall for that monsoon season. This study indicates that the models could not predict the 2009 drought over India due to the use of less warm SST anomalies over the Pacific in the longer lead runs. Hence, it is proposed that the uncertainties in SST predictions (the lower boundary condition) have to be represented in the model predictions of summer monsoon rainfall over India.     

Origin of regional climate differences: role of boundary conditions and model formulation in two GCMs

Model differences in projections of extratropical regional climate change due to increasing greenhouse gases are investigated using two atmospheric general circulation models (AGCMs): ECHAM4 (Max Planck Institute, version 4) and CCM3 (National Center for Atmospheric Research Community Climate Model version 3). Sea-surface temperature (SST) fields calculated from observations and coupled versions of the two models are used to force each AGCM in experiments based on time-slice methodology. Results from the forced AGCMs are then compared to coupled model results from the Coupled Model Intercomparison Project 2 (CMIP2) database. The time-slice methodology is verified by showing that the response of each model to doubled CO₂ and SST forcing from the CMIP2 experiments is consistent with the results of the coupled GCMs. The differences in the responses of the models are attributed to (1) the different tropical SST warmings in the coupled simulations and (2) the different atmospheric model responses to the same tropical SST warmings. Both are found to have important contributions to differences in implied Northern Hemisphere (NH) winter extratropical regional 500 mb height and tropical precipitation climate changes. Forced teleconnection patterns from tropical SST differences are primarily responsible for sensitivity differences in the extratropical North Pacific, but have relatively little impact on the North Atlantic. There are also significant differences in the extratropical response of the models to the same tropical SST anomalies due to differences in numerical and physical parameterizations. Differences due to parameterizations dominate in the North Atlantic. Differences in the control climates of the two coupled models from the current climate, in particular for the coupled model containing CCM3, are also demonstrated to be important in leading to differences in extratropical regional sensitivity.     

FGOALS-g3模拟的南亚夏季风:气候态和年际变率

南亚夏季风的变化决定着印度半岛的旱涝状况,气候系统模式则是研究南亚夏季风变化规律的重要工具。本文基于观测和JRA55再分析资料,系统评估了FGOALS-g3模式模拟的南亚夏季风气候态和年际变率,并重点关注FGOALS-g3与FGOALS-g2以及是否考虑海气相互作用的模拟差异。结果表明,由于局地海温模拟的变化,相比于FGOALS-g2,FGOALS-g3模拟的南亚夏季风在气候态热带印度洋信风和El Ni?o期间沃克环流下沉支上有明显改进。同时,由于对流层系统性冷偏差持续存在并且中心位于副热带300 hPa附近,造成气候态上经向温度梯度减弱,使季风环流减弱,导致FGOALS-g3中陆地季风槽的水汽辐散偏差和降水干偏差仍然存在;在年际变率上,FGOALS-g3模拟的El Ni?o期间赤道西太平洋海温冷异常偏弱,印度洋偶极子偏强,导致印度半岛下沉运动减弱,FGOALS-g3中ENSO—印度降水负相关关系也依然偏弱。研究表明,耦合过程导致的气候态海温偏差通过改变环流和水汽输送,有效补偿了大气模式中印度半岛中部和中南半岛的降水湿偏差;在年际变率上,耦合模式由于考虑了海温—降水—云短波辐射的负反馈过程,能够减小大气模式模拟偏差的强度,但印太暖池区海温模拟偏差导致沃克环流下沉支偏西,使得印度半岛的降水响应出现更大的湿偏差。     

The representation of the South Tropical Atlantic teleconnection to the Indian Ocean in the AR4 coupled models

A series of recent papers showed that sea surface temperature (SST) anomalies in the south equatorial tropical Atlantic modulate the interannual variability of the African and Indian monsoon rainfall. Physically this teleconnection can be explained by a simple Gill-Matsuno mechanism. In this work, the output from five different models chosen within the CMIP3 (Coupled Model Intercomparison Project version 3) ensemble of coupled general circulation models (CGCMs) are analyzed to investigate how state-of-the-art CGCMs represent the impact of the South Tropical Atlantic (STA) SSTs on the Indian and African region. Using a correlation-regression technique, it is found that four out of the five models display a teleconnection between STA and Indian region which is generally weaker than in the observations but in agreement in the rainfall field pattern. This teleconnection is also noticeable in the ensemble mean of the five models. Over Africa, however, the significant changes in rainfall displayed in the observation are properly caught by only one of the CGCMs. Additionally, none of the models reproduces the symmetric upper-level wind response around the Equator seen over the Indian Ocean in the observations and all have significant biases also in the surface pressure field response to the tropical Atlantic SSTs. Nonetheless the STA response, particularly over the southern hemisphere, is indicative of the Gill-Matsuno-type mechanism identified in previous studies using idealized experiments with atmospheric GCMs and observational data. With a suite of atmospheric-only GCM integrations it is shown that the differences in amplitude and pattern are not only due to the strong biases and reduced variabilities of the CGCMs over the tropical Atlantic but they are also caused by the different physical parameterizations used in models.     

Impact of land–surface processes on the interannual variability of tropical climate in the LMD GCM

Tropical monsoon circulations exhibit substantial interannual variability. Establishing clear links between this variability and the slowly varying boundary forcing (sea surface temperatures, SSTs, and land surface conditions) has proved difficult. For example, no clear relationships have been found between SST anomalies associated with El Nino/La Nina events and monsoon rainfall. Despite much research over the past 50 years, there are still questions regarding how different components of the land-atmosphere-ocean system contribute to tropical monsoon variability. This study examines the question of land-surface-atmosphere interactions in large-scale tropical convection and their role in rainfall interannual variability. The analysis method is based on a conceptual model of convection energetics applied every day of the simulation at the grid points within the region of interest. This allows for a distinction between the frequency and the characteristic energy and water cycle of these events. With two ensembles of five and three experiments in which different land-surface schemes are used, the relation between land-surface processes and variation of the frequency of convection is studied. It has been found in this modeling study that the formulation of land surface schemes may be important for both the simulation of mean tropical precipitation and its interannual variability by way of the frequency of convective events. Linked to this is an increased response of hydrological cycle over land to SSTAs. Numerous studies have suggested that large-scale factors, such as SST, are the dominant control. However the influence of surface processes depends on the areal extent and distance that separates the region from the ocean. The fact that differences between tropical regions decreases as convection intensifies strengthens this hypothesis. The conclusion is that it is inappropriate to separate the causes of interannual variability between SSTAs and land-surface anomalies to explain precipitation variations as land surface processes play a significant mediating role in the relationship between SSTs and monsoon strength. However there remains the possibility that a substantial portion of variability is due to dynamical processes internal to the atmosphere. Determining the relative roles of internal and lower boundary forcing processes in producing interannual variations in the tropical climate is a major objective of future research.     

An examination of internally generated variability in long climate simulations

General circulation model experiments designed to estimate the magnitude and structure of internally generated variability and to help understand the mechanisms underlying this variability are described. The experiments consist of three multi-century integrations of a rhomboidal 15, 9 level, version of the Center for Ocean-Land-Atmosphere Studies atmospheric general circulation model: a run with fixed sea surface temperatures and equinox solar radiation, a run with seasonally varying climatological sea surface temperatures and seasonally varying solar forcing, and a run with seasonally varying solar forcing in which the state of the ocean is predicted by a 3° by 3°, 16 vertical level, nearly global domain version of the Geophysical Fluid Dynamics Laboratory Modular Ocean Model. No flux correction is used in the coupled model integration. Selected surface fields of the three runs are compared to each other as well as to the observed climate. Statistical properties of variability on interannual time scales are compared between the runs. Evidence is presented that climate time scale variability in the simulations is produced by random weather time scale forcing due to the integrating effect of elements of the system with long memories. The importance of ocean variability for land climate variability is demonstrated and attributed to both the memory effect and coupled atmosphere-ocean instability.     

Twentieth century Walker Circulation change: data analysis and model experiments

Recent studies indicate a weakening of the Walker Circulation during the twentieth century. Here, we present evidence from an atmospheric general circulation model (AGCM) forced by the history of observed sea surface temperature (SST) that the Walker Circulation may have intensified rather than weakened. Observed Equatorial Indo-Pacific Sector SST since 1870 exhibited a zonally asymmetric evolution: While the eastern part of the Equatorial Pacific showed only a weak warming, or even cooling in one SST dataset, the western part and the Equatorial Indian Ocean exhibited a rather strong warming. This has resulted in an increase of the SST gradient between the Maritime Continent and the eastern part of the Equatorial Pacific, one driving force of the Walker Circulation. The ensemble experiments with the AGCM, with and without time-varying external forcing, suggest that the enhancement of the SST gradient drove an anomalous atmospheric circulation, with an enhancement of both Walker and Hadley Circulation. Anomalously strong precipitation is simulated over the Indian Ocean and anomalously weak precipitation over the western Pacific, with corresponding changes in the surface wind pattern. Some sensitivity to the forcing SST, however, is noticed. The analysis of twentieth century integrations with global climate models driven with observed radiative forcing obtained from the Coupled Model Intercomparison Project (CMIP) database support the link between the SST gradient and Walker Circulation strength. Furthermore, control integrations with the CMIP models indicate the existence of strong internal variability on centennial timescales. The results suggest that a radiatively forced signal in the Walker Circulation during the twentieth century may have been too weak to be detectable.     

Intraseasonal SST-precipitation relationship and its spatial variability over the tropical summer monsoon region

The SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled models. The model also exhibits reasonable skill in simulating coherent northward propagating monsoon intraseasonal anomalies including SST and precipitation, which are generally consistent with observed ISV characteristics. Results from the observations and the model establish the existence of spatial variability in the atmospheric convective response to SST anomalies, over the Asian monsoon domain on intraseasonal timescales. The response is fast over the Arabian Sea, where precipitation lags SST by ~5 days; whereas it is slow over the Bay of Bengal and South China Sea, with a lag of ~12 days. The intraseasonal SST anomalies result in a similar atmospheric response across the basins, which consists of a destabilization of the bottom of the atmospheric column, as observed from the equivalent potential temperature anomalies near the surface. However, the presence of a relatively strong surface convergence over the Arabian Sea, due to the presence of a strong zonal gradient in SST, which accelerates the upward motion of the moist air, results in a relatively faster response in terms of the local precipitation anomalies over the Arabian Sea than over the Bay of Bengal and South China Sea. With respect to the observations, the ocean–atmosphere coupling is well simulated in the model, though with an overestimation of the intraseasonal SST anomalies, leading to an exaggerated SST-precipitation relationship. A detailed examination points to a systematic bias in the thickness of the mixed layer of the ocean model, which needs to be rectified. A too shallow (deep) mixed layer enhances (suppress) the amplitude of the intraseasonal SST anomalies, thereby amplifying (lessening) the ISV and the active-break phases of the monsoon in the model.     

Indian Ocean SST, evaporation, and precipitation during the South Asian summer monsoon in IPCC-AR4 coupled simulations

The veracity of modeled air–sea interactions in the Indian Ocean during the South Asian summer monsoon is examined. Representative simulations of the twentieth century climate, produced by coupled general circulation models as part of the Intergovernmental Panel on Climate Change Fourth Assessment Report, are the analysis targets along with observational data. The analysis shows the presence of large systematic biases in coupled simulations of boreal summer precipitation, evaporation, and sea surface temperature (SST) in the Indian Ocean, often exceeding 50% of the climatological values. Many of the biases are pervasive, being common to most simulations. The representation of air–sea interactions is also compromised. Coupled models tend to emphasize local forcing in the Indian Ocean as reflected by their large precipitation–SST correlations, at odds with the weak links in observations which suggest the importance of non-local controls. The evaporation–SST correlations are also differently represented, indicating atmospheric control on SST in some models and SST control on evaporation in others. The Indian monsoon rainfall–SST links are also misrepresented: the former is essentially uncorrelated with antecedent and contemporaneous Indian Ocean SSTs in nature, but not so in most of the simulations. Overall, coupled models are found deficient in portraying local and non-local air–sea interactions in the Indian Ocean during boreal summer. In our opinion, current models cannot provide durable insights on regional climate feedbacks nor credible projections of regional hydroclimate variability and change, should these involve ocean–atmosphere interactions in the Indian basin.     

Influence of SST biases on future climate change projections

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.     

Sensitivity of seasonal climate forecasts to persisted SST anomalies

Most estimates of the skill of atmospheric general circulation models (AGCMs) for forecasting seasonal climate anomalies have been based on simulations with actual observed sea surface temperatures (SSTs) as lower boundary forcing. Similarly estimates of the climatological response characteristics of AGCMs used for seasonal-to-interannual climate prediction generally rest on historical simulations using "perfect" SST forecasts. This work examines the errors and biases introduced into the seasonal precipitation response of an AGCM forced with persisted SST anomalies, which are generally considered to constitute a good prediction of SST in the first three-month season. The added uncertainty introduced by the persisted SST anomalies weakens, and in some cases nullifies, the skill of atmospheric predictions that is possible given perfect SST forcing. The use of persisted SST anomalies also leads to changes in local signal-to-noise characteristics. Thus, it is argued that seasonal-to-interannual forecasts using AGCMs should be interpreted relative to historical runs that were subject to the same strategy of boundary forcing used in the current forecast in order to properly account for errors and biases introduced by the particular SST prediction strategy. Two case studies are examined to illustrate how the sensitivity of the climate response to predicted SSTs may be used as a diagnostic to suggest improvements to the predicted SSTs.     

Uncertainties in modelling future hydrological change over West Africa

The aim of this paper is to evaluate current knowledge and uncertainties associated with the impact of increasing greenhouse gas and aerosol concentrations on the West African monsoon. For this purpose, coupled and time-slice simulations are used. A global measure of the monsoon changes is defined in order to avoid regional biases and to try and obtain significant results. The position and width of the monsoon in latitude are the main focuses. There is almost no agreement between the Coupled General Circulation models from the Coupled models Inter-Comparison project—Phase II in regard to the impact of climate change on the monsoon. Moreover, very simple discriminations between the models seem inappropriate to get a better signal. The role of the different forcings in time-slice simulations is then investigated. The sea surface temperature (SST) and particularly the pattern of the SST are shown to be the most important forcing. This accounts for the diversity of the results either from the coupled or the forced simulations with different SST changes. With a fixed SST, but of a smaller magnitude in AMJ, there are still uncertainties, coming first from the Atmospheric General Circulation models and the way they balance greenhouse gas and global SST increase. Finally the uncertainty due to the Land Surface models (LSMs) is not negligible. The greenhouse gas and the LSMs are shown to have more impact in August, when the monsoon is at its highest latitude on the continent.