Ability Of Global Climate Models Research Articles

Hot and dry compound events in South America: present climate and future projections, and their association with the Pacific Ocean

Compound hot and dry events can cause greater impacts than those generated by individual extreme events. Understanding the physical mechanisms that lead to their development is particularly important for an early warning. The aim of this study is to assess the ability of global climate models (GCMs) to simulate hot/dry compound events in South America (SA) during the historical period 1979–2014, in comparison with observational and reanalysis datasets. Additionally, this work seeks to investigate the potential changes in these events under two future climate scenarios for the period 2065–2100. Furthermore, we analyze the spatial patterns of sea surface temperature anomalies (SSTA) in the Pacific Ocean associated with these events in tropical and extratropical SA. In the historical period, reanalysis tends to overestimate the number of hot/dry events, while the ensemble median of GCMs performs better than the individual ones. The future projections under the high emissions scenario show longer heat waves, but a low model agreement about the number of compound events in tropical SA. For southern SA, an increase in the annual frequency of compound events is projected, and more than two hot/dry events per year are expected to occur relative to the 1979–2014 baseline. Finally, we find that compound events in tropical SA are favored during the El Niño phase, even though two other SSTA patterns have gained prominence in recent years. In southern SA, hot/dry events are associated with the negative phase of the Pacific Decadal Oscillation and the La Niña phase.

Common Error Patterns in the Regional Atmospheric Circulation Simulated by the CMIP Multi‐Model Ensemble

AbstractThe ability of global climate models to reproduce recurrent regional atmospheric circulation types is introduced as an overarching concept to explore potential dependencies between these models. If this approach is applied on a sufficiently large spatial domain, the similarity of the resulting error pattern can be compared from one model to another. By computing a pattern correlation matrix for a large multi‐model ensemble from the Coupled Model Intercomparison Project Phases 5 and 6, groups of comparatively strong correlation coefficients are obtained for those models working with similar atmospheric components. Thereby, frequent shared error patterns are found within the ensemble, which also occur for nominally different atmospheric component models. The error pattern correlation coefficients describing these similarities are nearly unrelated to model performance and can be used as statistical dependency weights.

A New Perspective on Coastally Trapped Disturbances Using Data from the Satellite Era

Abstract The ability of global climate models to simulate accurately marine stratiform clouds continues to challenge the atmospheric science community. These cloud types, which account for a large uncertainty in Earth’s radiation budget, are generally difficult to characterize due to their shallowness and spatial inhomogeneity. Previous work investigating marine boundary layer (MBL) clouds off the California coast has focused on clouds that form under the typical northerly flow regime during the boreal warm season. From about June through September, however, these northerly winds may reverse and become southerly as part of a coastally trapped disturbance (CTD). As the flow surges northward, it is accompanied by a broad cloud deck. Because these events are difficult to forecast, in situ observations of CTDs are few and far between, and little is known about their cloud physical properties. A climatological perspective of 23 CTD events—spanning the years from 2004 to 2016—is presented using several data products, including model reanalyses, buoys, and satellites. For the first time, satellite retrievals suggest that CTD cloud decks may play a unique role in the radiation budget due to a combination of aerosol sources that enhance cloud droplet number concentration and reduce cloud droplet effective radius. This particular type of cloud regime should therefore be treated differently than that which is more commonly found in the summertime months over the northeast Pacific Ocean. The potential influence of a coherent wind stress cycle on sea surface temperatures and sea salt aerosol is also explored.

Recent Tropical Expansion: Natural Variability or Forced Response?

AbstractPrevious studies have documented a poleward shift in the subsiding branches of Earth’s Hadley circulation since 1979 but have disagreed on the causes of these observed changes and the ability of global climate models to capture them. This synthesis paper reexamines a number of contradictory claims in the past literature and finds that the tropical expansion indicated by modern reanalyses is within the bounds of models’ historical simulations for the period 1979–2005. Earlier conclusions that models were underestimating the observed trends relied on defining the Hadley circulation using the mass streamfunction from older reanalyses. The recent observed tropical expansion has similar magnitudes in the annual mean in the Northern Hemisphere (NH) and Southern Hemisphere (SH), but models suggest that the factors driving the expansion differ between the hemispheres. In the SH, increasing greenhouse gases (GHGs) and stratospheric ozone depletion contributed to tropical expansion over the late twentieth century, and if GHGs continue increasing, the SH tropical edge is projected to shift further poleward over the twenty-first century, even as stratospheric ozone concentrations recover. In the NH, the contribution of GHGs to tropical expansion is much smaller and will remain difficult to detect in a background of large natural variability, even by the end of the twenty-first century. To explain similar recent tropical expansion rates in the two hemispheres, natural variability must be taken into account. Recent coupled atmosphere–ocean variability, including the Pacific decadal oscillation, has contributed to tropical expansion. However, in models forced with observed sea surface temperatures, tropical expansion rates still vary widely because of internal atmospheric variability.

A Statistical Assessment of Southern Hemisphere Tropical Cyclone Tracks in Climate Models

Reliable projections of future changes in tropical cyclone (TC) characteristics are highly dependent on the ability of global climate models (GCMs) to simulate the observed characteristics of TCs (i.e., their frequency, genesis locations, movement, and intensity). Here, we investigate the performance of a suite of GCMs from the U.S. CLIVAR Working Group on Hurricanes in simulating observed climatological features of TCs in the Southern Hemisphere. A subset of these GCMs is also explored under three idealized warming scenarios. Two types of simulated TC tracks are evaluated on the basis of a commonly applied cluster analysis: 1) explicitly simulated tracks, and 2) downscaled tracks, derived from a statistical–dynamical technique that depends on the models’ large-scale environmental fields. Climatological TC properties such as genesis locations, annual frequency, lifetime maximum intensity (LMI), and seasonality are evaluated for both track types. Future changes to annual frequency, LMI, and the latitude of LMI are evaluated using the downscaled tracks where large sample sizes allow for statistically robust results. An ensemble approach is used to assess future changes of explicit tracks owing to their small number of realizations. We show that the downscaled tracks generally outperform the explicit tracks in relation to many of the climatological features of Southern Hemisphere TCs, despite a few notable biases. Future changes to the frequency and intensity of TCs in the downscaled simulations are found to be highly dependent on the warming scenario and model, with the most robust result being an increase in the LMI under a uniform 2°C surface warming.

Evaluating climate model simulations of drought for the northwestern United States

ABSTRACTProjected changes in regional characteristics of drought throughout the 21st century can help inform climate change assessments across drought‐sensitive sectors. However, the ability of global climate models (GCMs) to reproduce statistical attributes of observed drought at regional scales has not typically been considered. We present a framework for evaluating the fidelity of GCMs to simulate regional drought to help guide model selection for users of regional climate projections where drought plays a key climate impact, and elucidate shortcomings of model simulations of hydroclimate variability. Monthly precipitation (Pr) and potential evapotranspiration (ETo) from 24 GCMs of the Coupled Model Intercomparison Project Phase 5 were compared to observations, with a focus on the northwestern United States (NWUS), using a suite of statistics for capturing multi‐scalar aspects of drought and both supply (Pr) and atmospheric demand (ETo). Model fidelity was generally higher for drought metrics evaluated with ETo versus Pr, and for seasonal and annual time scales versus multi‐year time scales. While some GCMs performed well across the suite of drought metrics and time scales, models systematically underestimated the severity of regional drought in the NWUS defined by precipitation deficits, particularly for multi‐year time scales.

Regional and large-scale influences on seasonal to interdecadal variability in Caribbean surface air temperature in CMIP5 simulations

We evaluate the ability of global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) to reproduce observed seasonality and interannual variability of temperature over the Caribbean, and compare these with simulations from atmosphere-only (AMIP5) and previous-generation CMIP3 models. Compared to station and gridded observations, nearly every CMIP5, CMIP3 and AMIP5 simulation tends to reproduce the primary inter-regional features of the Caribbean annual temperature cycle. In most coupled model simulations, however, boreal summer temperature lags observations by about 1 month, with a similar lag in the simulated annual cycle of sea surface temperature (SST), and a systematic cold bias in both climatological annual mean air temperature and SST. There is some improvement from CMIP3 to CMIP5 but the bias is still marked compared to AMIP5 and observations, implying that biases in the annual temperature cycle may originate in the ocean component of the coupled models. This also suggests a tendency for models to over-emphasize the influence of SSTs on near-surface temperature, a bias that may be exacerbated by model tendency to over-estimate ocean mixed layer depth as well. In contrast, we find that both coupled and atmosphere-only models tend to reasonably simulate the response of observed temperature to global temperature, to regional and large-scale variability across the Caribbean region and the Gulf of Mexico, and even to more remote Atlantic and Pacific influences. These findings contribute to building confidence in the ability of coupled models to simulate the effect of global-scale change on the Caribbean.

Autumn Precipitation Trends over Southern Hemisphere Midlatitudes as Simulated by CMIP5 Models

AbstractIn recent decades, Southern Hemisphere midlatitude regions such as southern Africa, southeastern Australia, and southern Chile have experienced a reduction in austral autumn precipitation; the cause of which is poorly understood. This study focuses on the ability of global climate models that form part of the Coupled Model Intercomparison Project phase 5 to simulate these trends, their relationship with extratropical and subtropical processes, and implications for future precipitation changes. Models underestimate both the historical autumn poleward expansion of the subtropical dry zone and the positive southern annular mode (SAM) trend. The multimodel ensemble (MME) is also unable to capture the spatial pattern of observed precipitation trends across semiarid midlatitude regions. However, in temperate regions that are located farther poleward such as southern Chile, the MME simulates observed precipitation declines. The MME shows a strong consensus in twenty-first-century declines in autumn precipitation across southern Chile in both the medium–low and high representative concentration pathway (RCP) scenarios and across southern Africa in the high RCP scenario, but little change across southeastern Australia. Projecting a strong positive SAM trend and continued subtropical dry-zone expansion, the models converge on large SAM and dry-zone-expansion-induced precipitation declines across southern midlatitudes. In these regions, the strength of future precipitation trends is proportional to the strength of modeled trends in these phenomena, suggesting that unabated greenhouse gas–induced climate change will have a large impact on austral autumn precipitation in such midlatitude regions.

Regional, Very Heavy Daily Precipitation in CMIP5 Simulations

Abstract The authors analyze the ability of global climate models (GCMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble to simulate very heavy daily precipitation and its supporting processes, comparing them with observations. Their analysis focuses on an upper Mississippi region for winter (December–February), when it is assumed that resolved synoptic circulation governs precipitation. CMIP5 GCMs generally reproduce well the precipitation versus intensity spectrum seen in observations to intensities as strong as 20 mm day−1. Most models do not produce the highest precipitation intensities seen in observations. Models show good agreement at the 95th percentile, while the coarsest resolution models generally show lower precipitation at high-intensity thresholds, such as the 99.5th percentile. There is no dominant month for simulated very heavy events to occur, although observed very heavy events occur most frequently in December. Further analysis focuses on precipitation events exceeding the 99.5th percentile that occur simultaneously at several points in the region, yielding so-called “widespread events.” Examination of additional fields during widespread very heavy events shows that the models produce these events under the same physical conditions seen in the observations. The coarsest models generally produce similar behavior, although features have smoother spatial distributions. However, the resolution in itself could not be identified as a major reason that separates one model from another. The capabilities of the CMIP5 GCMs examined here support using them to assess changes in very heavy precipitation under future climate scenarios.

Understanding the sources of Caribbean precipitation biases in CMIP3 and CMIP5 simulations

We assess the ability of Global Climate Models participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) to simulate observed annual precipitation cycles over the Caribbean. Compared to weather station records and gridded observations, we find that both CMIP3 and CMIP5 models can be grouped into three categories: (1) models that correctly simulate a bimodal distribution with two rainfall maxima in May–June and September–October, punctuated by a mid-summer drought (MSD) in July–August; (2) models that reproduce the MSD and the second precipitation maxima only; and (3) models that simulate only one precipitation maxima, beginning in early summer. These categories appear related to model simulation of the North Atlantic Subtropical High (NASH) and sea surface temperature (SST) in the Caribbean Sea and Gulf of Mexico. Specifically, models in category 2 tend to anticipate the westward expansion of the NASH into the Caribbean in early summer. Early onset of NASH results in strong moisture divergence and MSD-like conditions at the time of the May–June observed precipitation maxima. Models in category 3 tend to have cooler SST across the region, particularly over the central Caribbean and the Gulf of Mexico, as well as a weaker Caribbean low-level jet accompanying a weaker NASH. In these models, observed June-like patterns of moisture convergence in the central Caribbean and the Central America and divergence in the east Caribbean and the Gulf of Mexico persist through September. This analysis suggests systematic biases in model structure may be responsible for biases in observed precipitation variability over the Caribbean and more confidence may be placed in the precipitation simulated by the GCMs that are able to correctly simulate seasonal cycles of SST and NASH.

Do Climate Models Capture the Tropical Influences on North Pacific Sea Surface Temperature Variability?

Abstract This study evaluates the ability of global climate models to reproduce observed tropical influences on North Pacific Ocean sea surface temperature variability. In an ensemble of climate models, the study finds that the simulated North Pacific response to El Niño–Southern Oscillation (ENSO) forcing is systematically delayed relative to the observed response because of winter and spring mixed layers in the North Pacific that are too deep and air–sea feedbacks that are too weak. Model biases in mixed layer depth and air–sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by about 30%. The study also shows that simulated North Pacific variability has more power at lower frequencies than is observed because of model errors originating in the tropics and extratropics. Implications of these results for predictions on seasonal, decadal, and longer time scales are discussed.

Evaluating the Impacts of Global Warming on Geomorphological Systems

Ongoing climate change (global warming) is a major forcing factor on Earth’s ecological services including agricultural production, biodiversity, and carbon cycle. Climatic regime and climate change is also a major driver of the dynamics of Earth’s geomorphological systems, including its glaciers, rivers, mountains and coasts, especially over longer (103–105 year) time scales that correspond to climate forcing by orbital cycles. Many studies have considered how geomorphological systems have responded to climate forcing over long time scales, where system responses are approximately in phase with forcing (Lal 2004; Lowe et al. 2008). Over shorter time scales, however, geomorphological systems do not respond in phase with climate forcing, are affected by human (anthropogenic) activity, and yield nonlinear responses that cannot be fully predicted based on their previous behaviour (Perry 2002; Murray et al. 2009). The response of geomorphological systems to climate forcing can be examined by monitoring changes to their morphology and geomorphological processes during the recent past (last <150 years) for which instrumental climate data are available. This comparison allows for a more complete understanding of the relationship between climate forcing and geomorphological response. Global warming has given a new impetus to studies of climate forcing of geomorphological systems. This is because, despite the ability of global climate models (GCMs) to predict future temperature, precipitation and sea level, they do not consider likely responses of geomorphological (land surface) systems despite there being important feedbacks between surface processes and climate. These feedbacks include variations in snow/ice cover that result in changes to albedo and energy balance; changes in terrestrial ecosystems and land surface erosion that result in changes in carbon storage; and variations in continental weathering that lead to variations in cation flux to the ocean that influences its capacity for carbon dioxide (CO2) downdraw. Despite feedbacks being a significant source of uncertainty in GCMs (Boer and Yu 2003), the land surface conditions and geomorphological processes that give rise to these feedbacks are generally poorly known. GCMs do not consider the nature of the land surface, except at very broad scales, and cannot incorporate these feedbacks. Studies of geomorphological processes are usually based on small geographic areas, over short time scales, and are not closely linked to inputs or outputs from GCMs. Identifying the relationships between climate forcing and geomorphological response can yield a better understanding of the sensitivity of geomorphological systems to such forcing. Ongoing global warming in combination with landuse change, urbanisation and geoengineering, is now making geomorphological systems work at rates and within structural limitations unprecedented throughout human history. It is therefore critical to know how, where and at what rates these geomorphological systems will respond to climate and anthropogenic forcing. In this article, we describe how and why ongoing global warming is causing changes to the workings of geomorphological systems. We argue that the concept of geomorphological sensitivity is a useful means by which to understand why these changes occur, and provide a context for monitoring and modelling these changes into the future. This article first explains climate sensitivity from which we derive the concept of geomorphological sensitivity. We then apply this concept to consider how sediment yield changes as a result of climate forcing. A useful analogue for geomorphological system behaviour under present global warming is that of paraglacial processes under conditions of ice retreat. We argue that understanding the response of geomorphological systems to global warming has major implications for climate policy and adaption strategies.

Sea-ice thickness in the Weddell Sea, Antarctica: a comparison of model and upward-looking sonar data

AbstractSea-ice thickness is a key parameter for estimates of salt fluxes to the ocean and the contribution to global thermohaline circulation. Observations of sea-ice thickness in the Southern Ocean are sparse and difficult to collect. An exception to this data gap is time-series data from upward-looking sonars (ULS) which sample the drifting sea ice continuously. In this study we use ULS data from ten different locations over periods ranging from 9 to 25 months to compare with model data. Although these data are limited in space and time, they provide a qualitative indication of the ability of global climate models (GCMs) to adequately represent Southern Ocean sea ice. We compare the ULS data to output from four different GCMs (BCCR-BCM2.0, ECHAM5/MPI-OM, UKMO-HadCM3 and NCAR CCSM3) which were used for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. They simulate the ice thickness reasonably well, but in most cases average model ice thickness is less than thicknesses derived from ULS data. The seasonal cycle produced by the models correlates well with the ULS except for locations near Maud Rise, where in summer the ULS find a low concentration of thick ice floes. This overly thin ice will have implications for both the salt flux to the central Weddell Sea during the growth season and the freshwater flux during the melt season. Using satellite-derived ice-drift data to calculate transports in the Weddell Sea, we find that the underestimation of ice thickness results in underestimated salt fluxes.

Ability of global climate models at a regional scale over Australia

We evaluate the coupled climate models used in the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC). Our evaluation is focused on twelve regions of Australia for the daily simulation of precipitation, minimum temperature and maximum temperature. We base our evaluation on Probability Density Functions (PDFs). We introduce a simple quantitative measure of how well each climate model can capture the observed PDFs for each variable over Australia. Across all three variables, the coupled climate models perform better than we expected although one model is clearly flawed in simulating maximum temperature. An overall ranking of the climate models, for the three variables is presented. We therefore provide guidance on those climate models that are skillful over Australia, providing direction on those that should be used in impacts assessments where those impacts are based on precipitation or temperature.

CLIMATE CHANGE: A 1994 SCIENCE SUMMARY

New observations of the chemical composition of the atmosphere are reshaping scientific understanding of the global sources and sinks of the greenhouse gases. Current trends in the atmospheric concentrations of some of these gases are reviewed, with reference to new work emerging from Antarctic ice cores.Accompanying an understanding of the composition of the atmosphere, is the need to understand the processes which drive the global climate system, including interactions between the atmosphere and oceans. Studies of climatic processes therefore form the scientific underpinning for the development of numerical models that describe the response of the global climate system to observed changes in the composition of the atmosphere.Success or failure in efforts to improve model simulations can be assessed using a variety of objective statistical tests. Examples of such tests show demonstrable progress in the ability of global climate models to simulate the present day climate realistically.Since confidence in the regional details of climate predictions from climate models is low, considerable effort is being devoted to developing models capable of providing improved regional estimates of climate change and in practice a variety of models not limited to the global-scale models are used in this work. In the meantime, several approaches to assessing the potential impacts of climate change are possible. These are discussed with special reference to tropical cyclones and east coast lows.Throughout this review emphasis is placed on recent Australian contributions to the field, most notably work conducted within CSIRO.