Global seasonal climate predictability in a two tiered forecast system. Part II: boreal winter and spring seasons

We examine the Florida Climate Institute–Florida State University Seasonal Hindcast (FISH50) skill at a relatively high (50 km grid) resolution two tiered Atmospheric General Circulation Model (AGCM) for boreal winter and spring seasons at zero and one season lead respectively. The AGCM in FISH50 is forced with bias corrected forecast sea surface temperature averaged from two dynamical coupled ocean–atmosphere models. The comparison of the hindcast skills of precipitation and surface temperature from FISH50 with the coupled ocean–atmosphere models reveals that the probabilistic skill is nearly comparable in the two types of forecast systems (with some improvements in FISH50 outside of the global tropics). Furthermore the drop in skill in going from zero lead (boreal winter) to one season lead (boreal spring) is also similar in FISH50 and the coupled ocean–atmosphere models. Both the forecast systems also show that surface temperature hindcasts have more skill than the precipitation hindcasts and that land based precipitation hindcasts have slightly lower skill than the corresponding hindcasts over the ocean.     

The seasonal predictability of the Asian summer monsoon in a two-tiered forecast system

An extensive set of boreal summer seasonal hindcasts from a two tier system is compared with corresponding seasonal hindcasts from two other coupled ocean–atmosphere models for their seasonal prediction skill (for precipitation and surface temperature) of the Asian summer monsoon. The unique aspect of the two-tier system is that it is at relatively high resolution and the SST forcing is uniquely bias corrected from the multi-model averaged forecasted SST from the two coupled ocean–atmosphere models. Our analysis reveals: (a) The two-tier forecast system has seasonal prediction skill for precipitation that is comparable (over the Southeast Asian monsoon) or even higher (over the South Asian monsoon) than the coupled ocean–atmosphere. For seasonal anomalies of the surface temperature the results are more comparable across models, with all of them showing higher skill than that for precipitation. (b) Despite the improvement from the uncoupled AGCM all models in this study display a deterministic skill for seasonal precipitation anomalies over the Asian summer monsoon region to be weak. But there is useful probabilistic skill for tercile anomalies of precipitation and surface temperature that could be harvested from both the coupled and the uncoupled climate models. (c) Seasonal predictability of the South Asian summer monsoon (rainfall and temperature) does seem to stem from the remote ENSO forcing especially over the Indian monsoon region and the relatively weaker seasonal predictability in the Southeast Asian summer monsoon could be related to the comparatively weaker teleconnection with ENSO. The uncoupled AGCM with the bias corrected SST is able to leverage this teleconnection for improved seasonal prediction skill of the South Asian monsoon relative to the coupled models which display large systematic errors of the tropical SST’s.     

Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part II. predictability and prediction skill

The interdecadal change in seasonal predictability and numerical models’ seasonal forecast skill in the Northern Hemisphere are examined using both observations and the seasonal hindcast from six coupled atmosphere-ocean climate models from the 21 period of 1960–1980 (P1) to that of 1981–2001 (P2). It is shown that the one-month lead seasonal forecast skill of the six models’ multi-model ensemble is significantly increased from P1 to P2 for all four seasons. We identify four possible reasons accounting for the interdecadal change of the seasonal forecast skill. Firstly, the numerical model’s ability to simulate the mean state, the time variability and the spatial structures of the sea surface temperature and precipitation over the tropical Pacific is improved in P2 compared to P1. Secondly, an examination of the potential predictability of the atmosphere, estimated by the ratio of the total variance to the variance due to the internal dynamics of the model atmosphere, reveals that the atmospheric potential predictability is significantly increased after 1980s which is mainly due to an increased influence of El Niño-Southern Oscillation signal over the North Pacific and North American regions. Thirdly, the long-term climate trends in the atmosphere are found to contribute, to some extent, to the increased seasonal forecast skill especially over the Eurasian regions. Finally, the improved ocean observations in P2 may provide better initial conditions for the coupled models’ seasonal forecast.     

Abrupt change in climate regime from summer to fall 1985 and stability in the fall

Summary This paper treats a dramatic transition between the summer and fall of 1985 when temperature and precipitation anomaly patterns and the associated midtropospheric flow over the coterminous United States and adjacent oceans underwent a strong reversal. After this break in regime, the fall patterns locked into a remarkably stable state. It is interesting that this case confirms a more general statistical result from previous completely independent episodes. The hypothesis suggested to explain this strong change and its subsequent persistence draws upon air-sea interactions over the North Pacific and resulting downstream influences.With 11 FiguresPresented at Eleventh Diagnostic Workshop in Urbana, Illinois, U.S.A. on October 14–17, 1986.     

Relative contribution of soil moisture and snow mass to seasonal climate predictability: a pilot study

Land surface hydrology (LSH) is a potential source of long-range atmospheric predictability that has received less attention than sea surface temperature (SST). In this study, we carry out ensemble atmospheric simulations driven by observed or climatological SST in which the LSH is either interactive or nudged towards a global monthly re-analysis. The main objective is to evaluate the impact of soil moisture or snow mass anomalies on seasonal climate variability and predictability over the 1986–1995 period. We first analyse the annual cycle of zonal mean potential (perfect model approach) and effective (simulated vs. observed climate) predictability in order to identify the seasons and latitudes where land surface initialization is potentially relevant. Results highlight the influence of soil moisture boundary conditions in the summer mid-latitudes and the role of snow boundary conditions in the northern high latitudes. Then, we focus on the Eurasian continent and we contrast seasons with opposite land surface anomalies. In addition to the nudged experiments, we conduct ensembles of seasonal hindcasts in which the relaxation is switched off at the end of spring or winter in order to evaluate the impact of soil moisture or snow mass initialization. LSH appears as an effective source of surface air temperature and precipitation predictability over Eurasia (as well as North America), at least as important as SST in spring and summer. Cloud feedbacks and large-scale dynamics contribute to amplify the regional temperature response, which is however, mainly found at the lowest model levels and only represents a small fraction of the observed variability in the upper troposphere.     

Daily modes of South Asian summer monsoon variability in the NCEP climate forecast system

The leading modes of daily variability of the Indian summer monsoon in the climate forecast system (CFS), a coupled general circulation model, of the National Centers for Environmental Predictions (NCEP) are examined. The space?Ctime structures of the daily modes are obtained by applying multi-channel singular spectrum analysis (MSSA) on the daily anomalies of rainfall. Relations of the daily modes to intraseasonal and interannual variability of the monsoon are investigated. The CFS has three intraseasonal oscillations with periods around 106, 57 and 30?days with a combined variance of 7%. The 106-day mode has spatial structure and propagation features similar to the northeastward propagating 45-day mode in the observations except for its longer period. The 57-day mode, despite being in the same time scale as of the observations has poor eastward propagation. The 30-day mode is northwestward propagating and is similar to its observational counterpart. The 106-day mode is specific to the model and should not be mistaken for a new scale of variability in observations. The dominant interannual signal is related to El Ni?o-Southern Oscillation (ENSO), and, unlike in the observations, has maximum variance in the eastern equatorial Indian Ocean. Although the Indian Ocean Dipole (IOD) mode was not obtained as a separate mode in the rainfall, the ENSO signal has good correlations with the dipole variability, which, therefore, indicates the dominance of ENSO in the model. The interannual variability is largely determined by the ENSO signal over the regions where it has maximum variance. The interannual variability of the intraseasonal oscillations is smaller in comparison.     

Multi-year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC）. Part Ⅰ： Sensitivity Study

A modified version of the NCAR/RegCM2 has been developed at the National Climate Center （NCC）, China Meteorological Administration, through a series of sensitivity experiments and multi-year simulations and hindcasts, with a special emphasis on the adequate choice of physical parameterization schemes suitable for the East Asian monsoon climate. This regional climate model is nested with the NCC/IAP （Institute of Atmospheric Physics） T63 coupled GCM to make an experimental seasonal prediction for China and East Asia. The four-year （2001 to 2004） prediction results are encouraging. This paper is the first part of a two-part paper, and it mainly describes the sensitivity study of the physical process paraxneterization represented in the model. The systematic errors produced by the different physical parameterization schemes such as the land surface processes, convective precipitation, cloud-radiation transfer process, boundary layer process and large-scale terrain features have been identified based on multi-year and extreme flooding event simulations. A number of comparative experiments has shown that the mass flux scheme （MFS） and Betts-Miller scheme （BM） for convective precipitation, the LPMI （land surface process model I） and LPMII （land surface process model Ⅱ） for the land surface process, the CCM3 radiation transfer scheme for cloud-radiation transfer processes, the TKE （turbulent kinetic energy） scheme for the boundary layer processes and the topography treatment schemes for the Tibetan Plateau are suitable for simulations and prediction of the East Asia monsoon climate in rainy seasons. Based on the above sensitivity study, a modified version of the RegCM2 （RegCM_NCC） has been set up for climate simulations and seasonal predictions.     

Extremes and predictability in the European pre-industrial climate of a regional climate model

A high-resolution pre-industrial control simulation with the regional climate model REMO is analyzed in detail for different European subregions. To our knowledge, this is the first long pre-industrial control simulation by a regional climate model as well as at comparable resolution. We assess the ability of the climate model to reproduce the observed climate variability in various parts of the continent. In order to investigate the representation of extreme events in the model under pre-industrial greenhouse gas concentrations, selected seasons are examined with regard to the atmospheric circulation and other climatic characteristics that have contributed to the occurrences. A special focus is dedicated to land-atmosphere interactions. Extreme seasons are simulated by the model under various circumstances, some of them strongly resemble observed periods of extraordinary conditions like the summer 2003 or autumn 2006 in parts of Europe. The regional perspective turns out to be of importance when analyzing events that are constituted by meso-scale atmospheric dynamics. Moreover, the predictability of the European climate on seasonal to decadal time scales is examined by relating the statistics of surface variables to large-scale modes of variability impacting the North Atlantic sector like the Meridional Overturning Circulation, the El Niño Southern Oscillation, and the North Atlantic Oscillation. For this purpose, we introduce a measure of tail dependence that quantifies the correlation between extreme values in two variables that describe the state of the climate system. Significant dependence of extreme events can be detected in various situations.     

夏季亚洲-太平洋涛动的耦合模式模拟

亚洲-太平洋涛动是夏季欧亚大陆东部(15°—50°N,60°—120°E)与北太平洋上空(15°—50°N,180°—120°W)温度场反相变化的现象。亚洲-太平洋涛动指数由对流层上层(500—200 hPa)温度定义,反映了亚洲-太平洋纬向热力差异。基于一个全球海-气耦合模式FGOALS_gl的20世纪气候模拟试验结果,讨论了其对20世纪亚洲-太平洋涛动指数变化的模拟能力。结果表明,较之ERA-40再分析资料(1960—1999年),模式很好地刻画出上层温度场的平均态和主导模态的空间型。从趋势上看,模式对北太平洋上空温度的年代际变化和趋势模拟较好,但未能模拟出亚洲东部陆地上空的降温趋势。从频谱分析结果看,模拟的亚洲-太平洋涛动指数2—3,a的年际变率与再分析资料相当,5-7 a周期的变率较弱。模式能够较好地模拟出与亚洲-太平洋涛动指数相关的亚洲季风区气候异常。在20世纪模拟中,外强迫因子会改变耦合系统的年际变率,在自然因子强迫下亚洲-太平洋涛动指数的功率谱向低频方向增强,人为强迫因子的作用则相反。自然强迫因子和人为强迫因子在不同时期对亚洲-太平洋涛动年际和年代际变率的作用不同。在年际变率中人为强迫因子能够控制亚洲-太平洋涛动的变率使其不致过大;在年代际变率中人为强迫因子会增强自然强迫下亚洲-太平洋涛动的变率。模式上层温度的主导模态受ENSO调制,可能影响亚洲-太平洋涛动的年际变率。因此,模式对ENSO模拟能力的缺陷是制约模式对流层上层温度及亚洲-太平洋涛动指数变率的重要因素。     

Interdecadal change in the Northern Hemisphere seasonal climate prediction skill: part I. The leading forced mode of atmospheric circulation

Using observations and 1-month lead hindcast data from six coupled atmosphere–ocean climate models, this study investigates the interdecadal change in the leading maximum covariance analysis mode (MCA1) of atmospheric circulation in response to the changes in the El Niño and Southern Oscillation (ENSO) occurred around late 1970s. We focus on boreal winter climate variability and predictability over the North Pacific–North American (NPNA) region using December–January–February prediction initiated from November 1st in the period of 1960–1980 (P1) and 1981–2001 (P2). Observed analysis reveals that ENSO variability, the related tropical convective activity, and thus the MCA1 are considerably enhanced from P1 to P2. As a result, surface climate anomalies over the NPNA are more significantly correlated with the MCA1 in P2 than P1, particularly over North America. The six coupled models and their multi-model ensemble not only are capable of capturing the interdecadal change of the MCA1 and its relationship with surface air temperature and precipitation over the NPNA regions but also have significantly higher forecast skills for the MCA1 and the surface climate anomalies in P2 than P1. However, models have systematic biases in the spatial distribution of the MCA1. It is demonstrated that the interdecadal change in the MCA1 should contribute to the improved forecast skill of the NPNA climate during recent epoch.     

Boreal summer intraseasonal variability simulated in the NCEP climate forecast system: insights from moist static energy budget and sensitivity to convective moistening

The NCEP Climate Forecast System (CFS) with the relaxed Arakawa Schubert (RAS, hereafter referred to as CTRL) convection scheme of Moorthi and Suarez exhibits better performance in representing boreal summer tropical intraseasonal variability as compared with a simulation using simplified Arakawa–Schubert scheme. The intraseasonal moist static energy (MSE) budget is analyzed in this version of the CFS model (CTRL), which produces realistic eastward and northward propagation characteristics. The moist and thermodynamic processes involved in the maintenance and propagation of the poleward moving intraseasonal oscillation (ISO) disturbances are examined here. Budget diagnostics show that horizontal MSE advection is the principal component of the budget, contributing to the poleward movement of the convection. The injection of MSE moistens the atmosphere north of the convective area causing the poleward movement of convection by destabilization of the atmosphere. The moistening process is mainly contributed by the climatological wind acting on the anomalous moisture gradient as confirmed from the examination of moisture advection equation. While surface enthalpy fluxes (consisting of radiative and surface turbulent heat fluxes) maintain the ISO anomalies, they oppose the MSE tendency due to horizontal advection thus regulating the poleward propagation characteristics. In addition, the model results show that wind–evaporation feedback dominates over cloud–radiation feedback for ISO propagation; this is in contrast to our estimates using the newly available European Centre for Medium Range Weather Forecasts Interim reanalysis. Sensitivity experiments suggest that intraseasonal variability in the CFS model with the RAS scheme is highly sensitive to the parameterization of both the shallow convection and the convective rain evaporation and downdrafts. Removal of these components adversely affects the propagation characteristics and greatly reduces the amplitude of intraseasonal variability. Our results support the primary importance of the moisture preconditioning ahead of the ISO and the physical relationship between moisture and precipitation. For realistic ISO simulations, models need to represent these features appropriately.     

The Interannual Variability and Predictability in a Global Climate Model

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Multi-Year Simulations and Experimental Seasonal Predictions for Rainy Seasons in China by Using a Nested Regional Climate Model （RegCM_NCC） Part Ⅱ： The Experimental Seasonal Prediction

A nested regional climate model has been experimentally used in the seasonal prediction at the China National Climate Center (NCC) since 2001. The NCC/IAP (Institute of Atmospheric Physics) T63 coupled GCM (CGCM) provides the boundary and initial conditions for driving the regional climate model (RegCM NCC). The latter has a 60-km horizontal resolution and improved physical parameterization schemes including the mass flux cumulus parameterization scheme, the turbulent kinetic energy closure scheme (TKE) and an improved land process model (LPM). The large-scale terrain features such as the Tibetan Plateau are included in the larger domain to produce the topographic forcing on the rain-producing systems. A sensitivity study of the East Asian climate with regard to the above physical processes has been presented in the first part of the present paper. This is the second part, as a continuation of Part I. In order to verify the performance of the nested regional climate model, a ten-year simulation driven by NCEP reanalysis datasets has been made to explore the performance of the East Asian climate simulation and to identify the model’s systematic errors. At the same time, comparative simulation experiments for 5 years between the RegCM2 and RegCM NCC have been done to further understand their differences in simulation performance. Also, a ten-year hindcast (1991–2000) for summer (June–August), the rainy season in China, has been undertaken. The preliminary results have shown that the RegCM NCC is capable of predicting the major seasonal rain belts. The best predicted regions with high anomaly correlation coefficient (ACC) are located in the eastern part of West China, in Northeast China and in North China, where the CGCM has maximum prediction skill as well. This fact may reflect the importance of the largescale forcing. One significant improvement of the prediction derived from RegCM NCC is the increase of ACC in the Yangtze River valley where the CGCM has a very low, even a negative, ACC. The reason behind this improvement is likely to be related to the more realistic representation of the large-scale terrain features of the Tibetan Plateau. Presumably, many rain-producing systems may be generated over or near the Tibetan Plateau and may then move eastward along the Yangtze River basin steered by upper-level westerly airflow, thus leading to enhancement of rainfalls in the mid and lower basins of the Yangtze River. The real-time experimental predictions for summer in 2001, 2002, 2003 and 2004 by using this nested RegCM NCC were made. The results are basically reasonable compared with the observations.     

Potential impacts of East Asian winter monsoon on climate variability and predictability in the Australian summer monsoon region

This study explores potential impacts of the East Asian winter monsoon (EAWM) on summer climate variability and predictability in the Australia–Asian region through Australia–Asia (A-A) monsoon interactions. Observational analysis is conducted for the period of 1959 to 2001 using ERA-40 wind reanalysis and Climate Research Unit rainfall and surface temperature monthly datasets. Statistically significant correlations are established between the Australian summer monsoon and its rainfall variations with cross-equatorial flows penetrating from South China Sea region and northerly flow in the EAWM. The underlying mechanism for such connections is the response of the position and intensity of Hardley circulation to strong/weak EAWM. A strong EAWM is associated with an enhanced cross-equatorial flow crossing the maritime continent and a strengthened Australia summer monsoon westerlies which affect rainfall and temperature variations in northern and eastern part of the Australian continent. Furthermore, partial correlation analysis, which largely excludes El Niño-Southern Oscillation (ENSO) effects, suggests that these connections are the inherent features in the monsoon system. This is further supported by analyzing a global model experiment using persistent sea surface temperatures (SSTs) which, without any SST interannual variations, shows similar patterns as in the observational analysis. Furthermore, such interaction could potentially affect climate predictability in the region, as shown by some statistically significant lag correlations at monthly time scale. Such results are attributed to the impacts of EAWM on regional SST variations and its linkage to surface conditions in the Eurasian continent. Finally, such impacts under global warmed climate are discussed by analyzing ten IPCC AR4 models and results suggest they still exist in the warmed climate even though the EAWM tends to be weaker.