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This study examines the possible relationship between predictions of weekly and biweekly averages of 10-m winds at 3-week lead time and interannual variability over the western Pacific and Indian Ocean (WP-IO) using Climate Forecast System version 2 (CFSv2) reforecasts for period 1979–2008. There is a large temporal correlation between forecasts and reanalyses for zonal, meridional, and total wind magnitudes at 10 m over most of WP-IO for the average of weeks 1 and 2 (W1 and W2) in reforecasts initialized in January (JIR) and May (MIR). The model has some correlations that exceed 95% confidence in some portions of WP-IO in week 3 (W3) but no skill in week 4 (W4) over most of the region. The model depicts prediction skill in the 14-day average of weeks 3–4 (W3–4) over portions of WP-IO, similar to the level of skill in W3. The amplitude of interannual variability (IAV) for 10-m winds in W1 of JIR and MIR is close to that in reanalyses. As lead time increases, the amplitude of IAV of 10-m winds gradually decreases over WP-IO in reforecasts, in contrast to behavior in reanalyses. The amplitude of IAV of predicted 10-m winds in W3–4 over WP-IO is equivalent to that in W3 and W4 in reforecasts. In contrast, the amplitude of IAV in W3–4 in January and May of the reanalysis is much smaller than IAV of W3 and W4. Therefore, one of the possible causes for prediction skill in W3–4 over subregions of WP-IO is due to a reduction of IAV bias in W3–4 in comparison to IAV bias in W3 and W4. [ABSTRACT FROM AUTHOR]

Project Athena is an international collaboration testing the efficacy of high-resolution global climate models. We compare results from 7-km mesh experiments of the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and 10-km mesh experiments of the Integrated Forecast System (IFS), focusing on the Intra-Seasonal Oscillation (ISO) and its relationship with tropical cyclones (TC) among the boreal summer period (21 May-31 Aug) of 8 years (2001-2002, 2004-2009). In the first month of simulation, both models capture the intra-seasonal oscillatory behavior of the Indian monsoon similar to the observed boreal summer ISO in approximately half of the 8-year samples. The IFS simulates the NW-SE-oriented rainband and the westerly location better, while NICAM marginally reproduces mesoscale organized convective systems and better simulates the northward migration of the westerly peak and precipitation, particularly in 2006. The reproducibility of the evolution of MJO depends on the given year; IFS simulates the MJO signal well for 2002, while NICAM simulates it well for 2006. An empirical orthogonal function analysis shows that both models statistically reproduce MJO signals similar to observations, with slightly better phase speed reproduced by NICAM. Stronger TCs are simulated in NICAM than in IFS, and NICAM shows a wind-pressure relation for TCs closer to observations. TC cyclogenesis is active during MJO phases 3 and 4 in NICAM as in observations. The results show the potential of high-resolution global atmospheric models in reproducing some aspects of the relationship between MJO and TCs and the statistical behavior of TCs. [ABSTRACT FROM AUTHOR]

The sensitivity to the horizontal resolution of the climate, anthropogenic climate change, and seasonal predictive skill of the ECMWF model has been studied as part of Project Athena-an international collaboration formed to test the hypothesis that substantial progress in simulating and predicting climate can be achieved if mesoscale and subsynoptic atmospheric phenomena are more realistically represented in climate models. In this study the experiments carried out with the ECMWF model (atmosphere only) are described in detail. Here, the focus is on the tropics and the Northern Hemisphere extratropics during boreal winter. The resolutions considered in Project Athena for the ECMWF model are T159 (126 km), T511 (39 km), T1279 (16 km), and T2047 (10 km). It was found that increasing horizontal resolution improves the tropical precipitation, the tropical atmospheric circulation, the frequency of occurrence of Euro-Atlantic blocking, and the representation of extratropical cyclones in large parts of the Northern Hemisphere extratropics. All of these improvements come from the increase in resolution from T159 to T511 with relatively small changes for further resolution increases to T1279 and T2047, although it should be noted that results from this very highest resolution are from a previously untested model version. Problems in simulating the Madden-Julian oscillation remain unchanged for all resolutions tested. There is some evidence that increasing horizontal resolution to T1279 leads to moderate increases in seasonal forecast skill during boreal winter in the tropics and Northern Hemisphere extratropics. Sensitivity experiments are discussed, which helps to foster a better understanding of some of the resolution dependence found for the ECMWF model in Project Athena. [ABSTRACT FROM AUTHOR]

During the summer of 2003, a record heat wave over Europe occurred, to which the deaths of over 20 000 people in 18 countries were attributed, 10 000 of those in France alone. Temperatures across Europe were above normal for most of the summer, but reached their peak during the first two weeks of August, when most of the deaths occurred. Ensemble simulations done with a recent version of the Center for Ocean-Land-Atmosphere Studies (COLA) atmospheric general circulation model (AGCM) have been analyzed over the European region. The simulations were forced by weekly mean observed sea surface temperature (SST). Relative to the 1982-2001 period, the COLA AGCM simulated anomalous warmth over the European region during June-August 2003, in response to the observed SST; however, the simulated magnitude was smaller than that observed. A series of simulations in which the observed SST was used only south of 25°N or only north of 25°N suggest that it was the influence of the local SST rather than remote SST that was an important influence on the heat wave. By early June, the soil over much of the European region was anomalously dry, consistent with the below-normal precipitation observed over the region in the preceding months. The model was restarted in early June with observation-based soil wetness anomalies imposed on the soil wetness from the control simulations. Although the model soil wetness was then allowed to evolve as usual, the simulations with the imposed initial soil wetness anomaly enhanced the simulated surface temperature anomaly during June-August by 1°-2°C. This weaker-than-observed temperature anomaly may be related to the persistence of imposed soil wetness anomalies, which was weaker than that observed. The experiments suggest that both the warm local SST and the dry local soil were important in intensifying the 2003 European heat wave. [ABSTRACT FROM AUTHOR]

The impending threat of global climate change and its regional manifestations is among the most important and urgent problems facing humanity. Society needs accurate and reliable estimates of changes in the probability of regional weather variations to develop science-based adaptation and mitigation strategies. Recent advances in weather prediction and in our understanding and ability to model the climate system suggest that it is both necessary and possible to revolutionize climate prediction to meet these societal needs. However, the scientific workforce and the computational capability required to bring about such a revolution is not available in any single nation. Motivated by the success of internationally funded infrastructure in other areas of science, this paper argues that, because of the complexity of the climate system, and because the regional manifestations of climate change are mainly through changes in the statistics of regional weather variations, the scientific and computational requirements to predict its behavior reliably are so enormous that the nations of the world should create a small number of multinational high-performance computing facilities dedicated to the grand challenges of developing the capabilities to predict climate variability and change on both global and regional scales over the coming decades. Such facilities will play a key role in the development of next-generation climate models, build global capacity in climate research, nurture a highly trained workforce, and engage the global user community, policy-makers, and stakeholders. We recommend the creation of a small number of multinational facilities with computer capability at each facility of about 20 peta-flops in the near term, about 200 petaflops within five years, and 1 exaflop by the end of the next decade. Each facility should have sufficient scientific workforce to develop and maintain the software and data analysis infrastructure. Such facilities will enable questions of what resolution, both horizontal and vertical, in atmospheric and ocean models, is necessary for more confident predictions at the regional and local level. Current limitations in computing power have placed severe limitations on such an investigation, which is now badly needed. These facilities will also provide the world's scientists with the computational laboratories for fundamental research on weather--climate interactions using 1-km resolution models and on atmospheric, terrestrial, cryospheric, and oceanic processes at even finer scales. Each facility should have enabling infrastructure including hardware, software, and data analysis support, and scientific capacity to interact with the national centers and other visitors. This will accelerate our understanding of how the climate system works and how to model it. It will ultimately enable the climate community to provide society with climate predictions, which are based on our best knowledge of science and the most advanced technology. [ABSTRACT FROM AUTHOR]

A multi-model set of atmospheric simulations forced by historical sea surface temperature (SST) or SSTs plus Greenhouse gases and aerosol forcing agents for the period of 1950–1999 is studied to identify and understand which components of the Asian–Australian monsoon (A–AM) variability are forced and reproducible. The analysis focuses on the summertime monsoon circulations, comparing model results against the observations. The priority of different components of the A–AM circulations in terms of reproducibility is evaluated. Among the subsystems of the wide A–AM, the South Asian monsoon and the Australian monsoon circulations are better reproduced than the others, indicating they are forced and well modeled. The primary driving mechanism comes from the tropical Pacific. The western North Pacific monsoon circulation is also forced and well modeled except with a slightly lower reproducibility due to its delayed response to the eastern tropical Pacific forcing. The simultaneous driving comes from the western Pacific surrounding the maritime continent region. The Indian monsoon circulation has a moderate reproducibility, partly due to its weakened connection to June–July–August SSTs in the equatorial eastern Pacific in recent decades. Among the A–AM subsystems, the East Asian summer monsoon has the lowest reproducibility and is poorly modeled. This is mainly due to the failure of specifying historical SST in capturing the zonal land-sea thermal contrast change across the East Asia. The prescribed tropical Indian Ocean SST changes partly reproduce the meridional wind change over East Asia in several models. For all the A–AM subsystem circulation indices, generally the MME is always the best except for the Indian monsoon and East Asian monsoon circulation indices. [ABSTRACT FROM AUTHOR]

The ability of atmospheric general circulation models (AGCMs), that are forced with observed sea surface temperatures (SSTs), to simulate the Indian monsoon rainfall (IMR) variability on interannual to decadal timescales is analyzed in a multimodel intercomparison. The multimodel ensemble has been performed within the CLIVAR International “Climate of the 20th Century” (C20C) Project. This paper is part of a C20C intercomparison of key climate time series. Whereas on the interannual timescale there is modest skill in reproducing the observed IMR variability, on decadal timescale the skill is much larger. It is shown that the decadal IMR variability is largely forced, most likely by tropical sea surface temperatures (SSTs), but as well by extratropical and especially Atlantic Multidecadal Oscillation (AMO) related SSTs. In particular there has been a decrease from the late 1950s to the 1990s that corresponds to a general warming of tropical SSTs. Using a selection of control integrations from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3), it is shown that the increase of greenhouse gases (GHG) in the twentieth century has not significantly contributed to the observed decadal IMR variability. [ABSTRACT FROM AUTHOR]

We use a simple methodology to test whether a set of atmospheric climate models with prescribed radiative forcings and ocean surface conditions can reproduce twentieth century climate variability. Globally, rapid land surface warming since the 1970s is reproduced by some models but others warm too slowly. In the tropics, air-sea coupling allows models to reproduce the Southern Oscillation but its strength varies between models. We find a strong relationship between the Southern Oscillation in global temperature and the rate of global warming, which could in principle be used to identify models with realistic climate sensitivity. This relationship and a weak response to ENSO suggests weak sensitivity to changes in sea surface temperature in some of the models used here. In the tropics, most models reproduce part of the observed Sahel drought. In the extratropics, models do not reproduce the observed increase in the North Atlantic Oscillation in response to forcings, through internal variability, or as a combination of both. [ABSTRACT FROM AUTHOR]

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework. [ABSTRACT FROM AUTHOR]

The article focuses on the World Climate Research Programme's World Modelling Summit for Climate Prediction, co-sponsored by World Weather Research Programme (WWRP) and the International Geosphere-Biosphere Programme (IGBP) held on May 6 to 9, 2008 in Reading, England. It cites that strategy development for climate prediction in dealing with climate change in regional standard is the primary objective of the summit. It also discusses the features of the proposed world Climate Prediction Project.

In this study, the authors address several issues with respect to the antecedent signals of the large-scale Asian summer monsoon that were earlier identified by Webster and Yang. In particular, they revisit the changes in the subtropical upper-tropospheric westerlies preceding the monsoon, depict the detailed structure of the monsoon's antecedent signals, and investigate the physical processes from the signals to the monsoon. They also explore the teleconnection of these signals to various large-scale climate phenomena and emphasize the importance of the upstream location of the signals relative to the Tibetan Plateau and the monsoon. Before a strong (weak) Asian summer monsoon, the 200-mb westerlies over subtropical Asia are weak (strong) during the previous winter and spring. A significant feature of these signals is represented by the variability of the Middle East jet stream whose changes are linked to the Arctic Oscillation, North Atlantic Oscillation, El Niño–Southern Oscillation, and other climate phenomena. When this jet stream intensifies and shifts southeastward, cold air intrudes frequently from eastern Europe into the Middle East and southwestern Asia. As a result, in subtropical Asia, snow and precipitation increase, the ground wetness increases, and surface temperature decreases. A strengthening Middle East jet stream is also accompanied by increases in both stationary wave activity flux and higher-frequency eddy activities. The Tibetan Plateau acts to block these westerly activities propagating eastward and increase the persistence of the low-temperature anomalies, which in turn prolongs the atmospheric signals from winter to spring. A strong link is found between the persistent low-temperature anomalies and the decrease in geopotential height over southern Asia, including the Tibetan Plateau, in spring. The latter indicates a late establishment of the South Asian high, and implies a delay in the atmospheric transition from winter to summer conditions and in the development of the summer monsoon. The preceding scenario for a strong Middle East jet stream and a weaker Asian monsoon can be applied accordingly for the discussion of the physical processes from a weak jet stream to a strong monsoon. The current results of the relationship between the extratropical process and Asian monsoon resemble several features of the tropical–extratropical interaction mechanism for the tropospheric biennial oscillation (TBO). While the role of tropical heating is emphasized in the TBO mechanism, compared to the variability of the sea surface temperature related to El Niño–Southern Oscillation, the extratropical process examined in this study is more strongly linked to the Asian summer monsoon. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Extracellular serine proteases, such as tissue-type plasminogen activator, plasmin or thrombin have been implicated as important regulators of various neural functions. In the developing nervous system, serine proteases regulate cell migration, axon growth and synapse formation. In the adult nervous system, a crucial involvement in synaptic plasticity associated with learning and memory operations, as well as excitotoxicity induced neuronal death has been reported. Localization of the neurotrypsin mRNA by in situ hybridization revealed its predominant expression in the nervous system.