482 resultados para global climate models
Resumo:
A common bias among global climate models (GCMs) is that they exhibit tropospheric southern annular mode (SAM) variability that is much too persistent in the Southern Hemisphere (SH) summertime. This is of concern for the ability to accurately predict future SH circulation changes, so it is important that it be understood and alleviated. In this two-part study, specifically targeted experiments with the Canadian Middle Atmosphere Model (CMAM) are used to improve understanding of the enhanced summertime SAM persistence. Given the ubiquity of this bias among comprehensive GCMs, it is likely that the results will be relevant for other climate models. Here, in Part I, the influence of climatological circulation biases on SAM variability is assessed, with a particular focus on two common biases that could enhance summertime SAM persistence: the too-late breakdown of the Antarctic stratospheric vortex and the equatorward bias in the SH tropospheric midlatitude jet. Four simulations are used to investigate the role of each of these biases in CMAM. Nudging and bias correcting procedures are used to systematically remove zonal-mean stratospheric variability and/or remove climatological zonal wind biases. The SAM time-scale bias is not alleviated by improving either the timing of the stratospheric vortex breakdown or the climatological jet structure. Even in the absence of stratospheric variability and with an improved climatological circulation, the model time scales are biased long. This points toward a bias in internal tropospheric dynamics that is not caused by the tropospheric jet structure bias. The underlying cause of this is examined in more detail in Part II of this study.
Resumo:
Many global climate models (GCMs) have trouble simulating Southern Annular Mode (SAM) variability correctly, particularly in the Southern Hemisphere summer season where it tends to be too persistent. In this two part study, a suite of experiments with the Canadian Middle Atmosphere Model (CMAM) is analyzed to improve our understanding of the dynamics of SAM variability and its deficiencies in GCMs. Here, an examination of the eddy-mean flow feedbacks is presented by quantification of the feedback strength as a function of zonal scale and season using a new methodology that accounts for intraseasonal forcing of the SAM. In the observed atmosphere, in the summer season, a strong negative feedback by planetary scale waves, in particular zonal wavenumber 3, is found in a localized region in the south west Pacific. It cancels a large proportion of the positive feedback by synoptic and smaller scale eddies in the zonal mean, resulting in a very weak overall eddy feedback on the SAM. CMAM is deficient in this negative feedback by planetary scale waves, making a substantial contribution to its bias in summertime SAM persistence. Furthermore, this bias is not alleviated by artificially improving the climatological circulation, suggesting that climatological circulation biases are not the cause of the planetary wave feedback deficiency in the model. Analysis of the summertime eddy feedbacks in the CMIP-5 models confirms that this is indeed a common problem among GCMs, suggesting that understanding this planetary wave feedback and the reason for its deficiency in GCMs is key to improving the fidelity of simulated SAM variability in the summer season.
Resumo:
We present a simple theoretical land-surface classification that can be used to determine the location and temporal behavior of preferential sources of terrestrial dust emissions. The classification also provides information about the likely nature of the sediments, their erodibility and the likelihood that they will generate emissions under given conditions. The scheme is based on the dual notions of geomorphic type and connectivity between geomorphic units. We demonstrate that the scheme can be used to map potential modern-day dust sources in the Chihuahuan Desert, the Lake Eyre Basin and the Taklamakan. Through comparison with observed dust emissions, we show that the scheme provides a reasonable prediction of areas of emission in the Chihuahuan Desert and in the Lake Eyre Basin. The classification is also applied to point source data from the Western Sahara to enable comparison of the relative importance of different land surfaces for dust emissions. We indicate how the scheme could be used to provide an improved characterization of preferential dust sources in global dust-cycle models.
Resumo:
Activities like the Coupled Model Intercomparison Project (CMIP) have revolutionized climate modelling in terms of our ability to compare models and to process information about climate projections and their uncertainties. The evaluation of models against observations is now considered a key component of multi-model studies. While there are a number of outstanding scientific issues surrounding model evaluation, notably the open question of how to link model performance to future projections, here we highlight a specific but growing problem in model evaluation - that of uncertainties in the observational data that are used to evaluate the models. We highlight the problem using an example obtained from studies of the South Asian Monsoon but we believe the problem is a generic one which arises in many different areas of climate model evaluation and which requires some attention by the community.
Resumo:
This paper aims to understand the physical processes causing the large spread in the storm track projections of the CMIP5 climate models. In particular, the relationship between the climate change responses of the storm tracks, as measured by the 2–6 day mean sea level pressure variance, and the equator-to-pole temperature differences at upper- and lower-tropospheric levels is investigated. In the southern hemisphere the responses of the upper- and lower-tropospheric temperature differences are correlated across the models and as a result they share similar associations with the storm track responses. There are large regions in which the storm track responses are correlated with the temperature difference responses, and a simple linear regression model based on the temperature differences at either level captures the spatial pattern of the mean storm track response as well explaining between 30 and 60 % of the inter-model variance of the storm track responses. In the northern hemisphere the responses of the two temperature differences are not significantly correlated and their associations with the storm track responses are more complicated. In summer, the responses of the lower-tropospheric temperature differences dominate the inter-model spread of the storm track responses. In winter, the responses of the upper- and lower-temperature differences both play a role. The results suggest that there is potential to reduce the spread in storm track responses by constraining the relative magnitudes of the warming in the tropical and polar regions.
Resumo:
The response of North Atlantic and European extratropical cyclones to climate change is investigated in the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). In contrast to previous multimodel studies, a feature-tracking algorithm is here applied to separately quantify the re- sponses in the number, the wind intensity, and the precipitation intensity of extratropical cyclones. Moreover, a statistical framework is employed to formally assess the uncertainties in the multimodel projections. Under the midrange representative concentration pathway (RCP4.5) emission scenario, the December–February (DJF) response is characterized by a tripolar pattern over Europe, with an increase in the number of cyclones in central Europe and a decreased number in the Norwegian and Mediterranean Seas. The June–August (JJA) response is characterized by a reduction in the number of North Atlantic cyclones along the southern flank of the storm track. The total number of cyclones decreases in both DJF (24%) and JJA (22%). Classifying cyclones according to their intensity indicates a slight basinwide reduction in the number of cy- clones associated with strong winds, but an increase in those associated with strong precipitation. However, in DJF, a slight increase in the number and intensity of cyclones associated with strong wind speeds is found over the United Kingdom and central Europe. The results are confirmed under the high-emission RCP8.5 scenario, where the signals tend to be larger. The sources of uncertainty in these projections are discussed.
Resumo:
The global mean temperature in 2008 was slightly cooler than that in 2007; however, it still ranks within the 10 warmest years on record. Annual mean temperatures were generally well above average in South America, northern and southern Africa, Iceland, Europe, Russia, South Asia, and Australia. In contrast, an exceptional cold outbreak occurred during January across Eurasia and over southern European Russia and southern western Siberia. There has been a general increase in land-surface temperatures and in permafrost temperatures during the last several decades throughout the Arctic region, including increases of 1° to 2°C in the last 30 to 35 years in Russia. Record setting warm summer (JJA) air temperatures were observed throughout Greenland. The year 2008 was also characterized by heavy precipitation in a number of regions of northern South America, Africa, and South Asia. In contrast, a prolonged and intense drought occurred during most of 2008 in northern Argentina, Paraguay, Uruguay, and southern Brazil, causing severe impacts to agriculture and affecting many communities. The year began with a strong La Niña episode that ended in June. Eastward surface current anomalies in the tropical Pacific Ocean in early 2008 played a major role in adjusting the basin from strong La Niña conditions to ENSO-neutral conditions by July–August, followed by a return to La Niña conditions late in December. The La Niña conditions resulted in far-reaching anomalies such as a cooling in the central tropical Pacific, Arctic Ocean, and the regions extending from the Gulf of Alaska to the west coast of North America; changes in the sea surface salinity and heat content anomalies in the tropics; and total column water vapor, cloud cover, tropospheric temperature, and precipitation patterns typical of a La Niña. Anomalously salty ocean surface salinity values in climatologically drier locations and anomalously fresh values in rainier locations observed in recent years generally persisted in 2008, suggesting an increase in the hydrological cycle. The 2008 Atlantic hurricane season was the 14th busiest on record and the only season ever recorded with major hurricanes each month from July through November. Conversely, activity in the northwest Pacific was considerably below normal during 2008. While activity in the north Indian Ocean was only slightly above average, the season was punctuated by Cyclone Nargis, which killed over 145,000 people; in addition, it was the seventh-strongest cyclone ever in the basin and the most devastating to hit Asia since 1991. Greenhouse gas concentrations continued to rise, increasing by more than expected based on with CO2 the 1979 to 2007 trend. In the oceans, the global mean uptake for 2007 is estimated to be 1.67 Pg-C, about CO2 0.07 Pg-C lower than the long-term average, making it the third-largest anomaly determined with this method since 1983, with the largest uptake of carbon over the past decade coming from the eastern Indian Ocean. Global phytoplankton chlorophyll concentrations were slightly elevated in 2008 relative to 2007, but regional changes were substantial (ranging to about 50%) and followed long-term patterns of net decreases in chlorophyll with increasing sea surface temperature. Ozone-depleting gas concentrations continued to fall globally to about 4% below the peak levels of the 2000–02 period. Total column ozone concentrations remain well below pre-1980, levels and the 2008 ozone hole was unusually large (sixth worst on record) and persistent, with low ozone values extending into the late December period. In fact the polar vortex in 2008 persisted longer than for any previous year since 1979. Northern Hemisphere snow cover extent for the year was well below average due in large part to the record-low ice extent in March and despite the record-maximum coverage in January and the shortest snow cover duration on record (which started in 1966) in the North American Arctic. Limited preliminary data imply that in 2008 glaciers continued to lose mass, and full data for 2007 show it was the 17th consecutive year of loss. The northern region of Greenland and adjacent areas of Arctic Canada experienced a particularly intense melt season, even though there was an abnormally cold winter across Greenland's southern half. One of the most dramatic signals of the general warming trend was the continued significant reduction in the extent of the summer sea-ice cover and, importantly, the decrease in the amount of relatively older, thicker ice. The extent of the 2008 summer sea-ice cover was the second-lowest value of the satellite record (which started in 1979) and 36% below the 1979–2000 average. Significant losses in the mass of ice sheets and the area of ice shelves continued, with several fjords on the northern coast of Ellesmere Island being ice free for the first time in 3,000–5,500 years. In Antarctica, the positive phase of the SAM led to record-high total sea ice extent for much of early 2008 through enhanced equatorward Ekman transport. With colder continental temperatures at this time, the 2007–08 austral summer snowmelt season was dramatically weakened, making it the second shortest melt season since 1978 (when the record began). There was strong warming and increased precipitation along the Antarctic Peninsula and west Antarctica in 2008, and also pockets of warming along coastal east Antarctica, in concert with continued declines in sea-ice concentration in the Amundsen/Bellingshausen Seas. One significant event indicative of this warming was the disintegration and retreat of the Wilkins Ice Shelf in the southwest peninsula area of Antarctica.
Resumo:
The main uncertainty in anthropogenic forcing of the Earth’s climate stems from pollution aerosols, particularly their ‘‘indirect effect’’ whereby aerosols modify cloud properties. We develop a new methodology to derive a measurement-based estimate using almost exclusively information from an Earth radiation budget instrument (CERES) and a radiometer (MODIS). We derive a statistical relationship between planetary albedo and cloud properties, and, further, between the cloud properties and column aerosol concentration. Combining these relationships with a data set of satellite-derived anthropogenic aerosol fraction, we estimate an anthropogenic radiative forcing of �-0.9 ± 0.4 Wm�-2 for the aerosol direct effect and of �-0.2 ± 0.1 Wm�-2 for the cloud albedo effect. Because of uncertainties in both satellite data and the method, the uncertainty of this result is likely larger than the values given here which correspond only to the quantifiable error estimates. The results nevertheless indicate that current global climate models may overestimate the cloud albedo effect.
Resumo:
The relationship between biases in Northern Hemisphere (NH) atmospheric blocking frequency and extratropical cyclone track density is investigated in 12 CMIP5 climate models to identify mechanisms underlying climate model biases and inform future model development. Biases in the Greenland blocking and summer Pacific blocking frequencies are associated with biases in the storm track latitudes while biases in winter European blocking frequency are related to the North Atlantic storm track tilt and Mediterranean cyclone density. However, biases in summer European and winter Pacific blocking appear less related with cyclone track density. Furthermore, the models with smaller biases in winter European blocking frequency have smaller biases in the cyclone density in Europe, which suggests that they are different aspects of the same bias. This is not found elsewhere in the NH. The summer North Atlantic and the North Pacific mean CMIP5 track density and blocking biases might therefore have different origins.
Resumo:
An online national survey among the Spanish population (n = 602) was conducted to examine the factors underlying a person’s support for commitments to global climate change reductions. Multiple hierarchical regression analysis was conducted in four steps and a structural equations model was tested. A survey tool designed by the Yale Project on Climate Change Communication was applied in order to build scales for the variables introduced in the study. The results show that perceived consumer effectiveness and risk perception are determinant factors of commitment to mitigating global climate change. However, there are differences in the influence that other factors, such as socio-demographics, view of nature and cultural cognition, have on the last predicted variable.
Resumo:
We investigate the initialization of Northern-hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates significantly reduces assimilation error both in identical-twin experiments and when assimilating sea-ice observations, reducing the concentration error by a factor of four to six, and the thickness error by a factor of two. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that the strong dependence of thermodynamic ice growth on ice concentration necessitates an adjustment of mean ice thickness in the analysis update. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that proportional mean-thickness updates are superior to the other two methods considered and enable us to assimilate sea ice in a global climate model using simple Newtonian relaxation.
Resumo:
We investigate the initialisation of Northern Hemisphere sea ice in the global climate model ECHAM5/MPI-OM by assimilating sea-ice concentration data. The analysis updates for concentration are given by Newtonian relaxation, and we discuss different ways of specifying the analysis updates for mean thickness. Because the conservation of mean ice thickness or actual ice thickness in the analysis updates leads to poor assimilation performance, we introduce a proportional dependence between concentration and mean thickness analysis updates. Assimilation with these proportional mean-thickness analysis updates leads to good assimilation performance for sea-ice concentration and thickness, both in identical-twin experiments and when assimilating sea-ice observations. The simulation of other Arctic surface fields in the coupled model is, however, not significantly improved by the assimilation. To understand the physical aspects of assimilation errors, we construct a simple prognostic model of the sea-ice thermodynamics, and analyse its response to the assimilation. We find that an adjustment of mean ice thickness in the analysis update is essential to arrive at plausible state estimates. To understand the statistical aspects of assimilation errors, we study the model background error covariance between ice concentration and ice thickness. We find that the spatial structure of covariances is best represented by the proportional mean-thickness analysis updates. Both physical and statistical evidence supports the experimental finding that assimilation with proportional mean-thickness updates outperforms the other two methods considered. The method described here is very simple to implement, and gives results that are sufficiently good to be used for initialising sea ice in a global climate model for seasonal to decadal predictions.