70 research outputs found
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Krakatau's long goodbye in the Ocean
State-of-the-art climate models suggest that 20th Century ocean warming and sea-level rise were substantially reduced by the 1883 eruption of Krakatau. Volcanically induced cooling of the ocean surface penetrated into deeper layers where it persisted for decades. We find that volcanic eruptions have longer lasting effects than previously suspected, sufficient to offset a large fraction of ocean warming and sea-level rise caused by anthropogenic influences over the 20th Century. We examine the latest suite of coupled ocean-atmosphere model experiments that include time-varying external forcings (e.g., changes in greenhouse gases, solar irradiance, sulfate aerosols and volcanic aerosols) for the period 1880-2000 (see Methods). These models have differences in physics, resolution, initial conditions, 'spin-up' and ocean-atmosphere coupling procedures, as well as different combinations of external forcings. Uncertainties in both the applied forcings and in the model responses to them are therefore inherent in our investigation
Systematizing the approach to air quality measurement and analysis in low and middle income countries
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Variability of Ocean Heat Uptake: Reconciling Observations and Models
This study examines the temporal variability of ocean heat uptake in observations and in climate models. Previous work suggests that coupled Atmosphere-Ocean General Circulation Models (A-OGCMs) may have underestimated the observed natural variability of ocean heat content, particularly on decadal and longer timescales. To address this issue, we rely on observed estimates of heat content from the 2004 World Ocean Atlas (WOA-2004) compiled by Levitus et al. (2005). Given information about the distribution of observations in WOA-2004, we evaluate the effects of sparse observational coverage and the infilling that Levitus et al. use to produce the spatially-complete temperature fields required to compute heat content variations. We first show that in ocean basins with limited observational coverage, there are important differences between ocean temperature variability estimated from observed and infilled portions of the basin. We then employ data from control simulations performed with eight different A-OGCMs as a test-bed for studying the effects of sparse, space- and time-varying observational coverage. Subsampling model data with actual observational coverage has a large impact on the inferred temperature variability in the top 300 and 3000 meters of the ocean. This arises from changes in both sampling depth and in the geographical areas sampled. Our results illustrate that subsampling model data at the locations of available observations increases the variability, reducing the discrepancy between models and observations
Chapter 10 - Detection and attribution of climate change: From global to regional
This chapter assesses the causes of observed changes assessed in Chapters 2 to 5 and uses understanding of physical processes, climate models and statistical approaches. The chapter adopts the terminology for detection and attribution proposed by the IPCC good practice guidance paper on detection and attribution (Hegerl et al., 2010) and for uncertainty Mastrandrea et al. (2011). Detection and attribution of impacts of climate changes are assessed by Working Group II, where Chapter 18 assesses the extent to which atmospheric and oceanic changes influence ecosystems, infrastructure, human health and activities in economic sectors
Rossby wave dynamics of the North Pacific extra-tropical response to El Niño: importance of the basic state in coupled GCMs
The extra-tropical response to El Nino in a "low" horizontal resolution coupled climate model, typical of the Intergovernmental Panel on Climate Change fourth assessment report simulations, is shown to have serious systematic errors. A high resolution configuration of the same model has a much improved response that is similar to observations. The errors in the low resolution model are traced to an incorrect representation of the atmospheric teleconnection mechanism that controls the extra-tropical sea surface temperatures (SSTs) during El Nino. This is due to an unrealistic atmospheric mean state, which changes the propagation characteristics of Rossby waves. These erroneous upper tropospheric circulation anomalies then induce erroneous surface circulation features over the North Pacific. The associated surface wind speed and direction errors create erroneous surface flux and upwelling anomalies which finally lead to the incorrect extra-tropical SST response to El Nino in the low resolution model. This highlights the sensitivity of the climate response to a single link in a chain of complex climatic processes. The correct representation of these processes in the high resolution model indicates the importance of horizontal resolution in resolving such processes
Extreme heat in India and anthropogenic climate change
On 19 May 2016 the afternoon temperature reached 51.0 !C in Phalodi in the northwest of India, a new record for the highest observed maximum temperature in India. The previous year, a widely-reported very lethal heat wave occurred in the southeast, in Andhra Pradesh and Telangana, killing thousands of people. In both cases it was widely assumed that the probability and severity of heat waves in India are increasing due to global warming, as they do in other parts of the world. However, we do not find positive trends in the highest maximum temperature of the year in most of India since the 1970s (except spurious trends due to missing data). Decadal variability cannot explain this, but both increased air pollution with aerosols blocking sunlight and increased irrigation leading to evaporative cooling have counteracted the effect of greenhouse gases up to now. Current climate models do not represent these processes well and hence cannot be used to attribute heat waves in this area.
The health effects of heat are often described better by a combination of temperature and humidity, such as a heat index or wet bulb temperature. Due to the increase in humidity from irrigation and higher SSTs these indices have increased over the last decades even when extreme temperatures have not. The extreme air pollution also exacerbates the health impacts of heat. From these factors it follows that, from a health impact point of view, the severity of heat waves has increased in India.
For the next decades we expect the trend due to global warming to continue, but the surface cooling effect of aerosols to diminish as air quality controls are implemented. The expansion of irrigation will likely continue, though at a slower pace, mitigating this trend somewhat. Humidity will probably continue to rise. The combination will give a strong rise of the temperature of heat waves. The high humidity will make health effects worse, whereas decreased air pollution would decrease the impacts.</p
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Half a degree additional warming, prognosis and projected impacts (HAPPI): Background and experimental design
Abstract. The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.
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Identifying causes of Western Pacific ITCZ drift in ECMWF System 4 hindcasts
The development of systematic biases in climate models used in operational seasonal forecasting adversely affects the quality of forecasts they produce. In this study, we examine the initial evolution of systematic biases in the ECMWF System 4 forecast model, and isolate aspects of the model simulations that lead to the development of these biases. We focus on the tendency of the simulated intertropical convergence zone in the western equatorial Pacific to drift northwards by between 0.5° and 3° of latitude depending on season. Comparing observations with both fully coupled atmosphere–ocean hindcasts and atmosphere-only hindcasts (driven by observed sea-surface temperatures), we show that the northward drift is caused by a cooling of the sea-surface temperature on the Equator. The cooling is associated with anomalous easterly wind stress and excessive evaporation during the first twenty days of hindcast, both of which occur whether air-sea interactions are permitted or not. The easterly wind bias develops immediately after initialisation throughout the lower troposphere; a westerly bias develops in the upper troposphere after about ten days of hindcast. At this point, the baroclinic structure of the wind bias suggests coupling with errors in convective heating, although the initial wind bias is barotropic in structure and appears to have an alternative origin
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Causes of Ocean Surface temperature Changes in Atlantic andPacific Topical Cyclogenesis Regions
Previous research has identified links between changes in sea surface temperature (SST) and hurricane intensity. We use climate models to study the possible causes of SST changes in Atlantic and Pacific tropical cyclogenesis regions. The observed SST increases in these regions range from 0.32 to 0.67 C over the 20th century. The 22 climate models examined here suggest that century-timescale SST changes of this magnitude cannot be explained solely by unforced variability of the climate system, even under conservative assumptions regarding the magnitude of this variability. Model simulations that include external forcing by combined anthropogenic and natural factors are generally capable of replicating observed SST changes in both tropical cyclogenesis regions
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