The diurnal cycle of surface air temperature in simulated present and doubled CO2 climates

 The diurnal range of surface air temperature (rT _a ) simulated for present and doubled CO₂ climates by the CSIRO9 GCM is analysed. Based on mean diurnal cycles of temperature and surface heat fluxes, a theory for understanding the results is developed. The cycles are described as the response to a diurnal forcing which is represented well by the diurnal mean flux of net shortwave radiation at the surface (SW) minus the evaporative (E) and sensible (H) fluxes. The response is modified by heat absorbed by the ground, and by the cycle in downward longwave (LW) radiation, but these effects are nearly proportional to the range in surface temperature. Thus in seasonal means, rT _a is approximately given by SW–E–H divided by 6 W m^-2/^°C. A multiple regression model for (rT _a ) is developed, based on quantities known to influence SW, E and H, and applied to both spatial variation in seasonal means, and day-to-day variation at a range of locations. In both cases, rT _a is shown to be influenced by cloud cover, snow extent and wind speed. It is influenced by soil moisture, although this effect is closely tied to that of cloud. In seasonal means rT _a is also well correlated with precipitable water, apparently because of the latter’s influence on E+H. The regression model describes well the spatial variation in the doubled CO₂ change in rT _a . The annual mean change in rT _a over land on doubling CO₂ was −0.36 ^°C, partly because of a decrease in the mean diurnal forcing (as defined in the theory), but also apparently because of the effect of nonlinearity in T _s of the upward longwave emission. A diagnostic radiation calculation indicates that the CO₂ and water vapour provide a small increase in rT _a through the downward LW response, which partially counters a decrease due to a reduction of SW by the gases. Received: 8 November 1995 / Accepted: 3 January 1997     

Long-term variations of surface air temperature at major industrial cities of India

Local temperature is one of the major climatic elements to record the changes in the atmospheric environment brought about by industrialization and urbanization. Long-term variations of seasonal and annual surface air temperature at six major industrial cities of India (Calcutta, Bombay, Madras, Bangalore, Pune and Delhi) have been studied, using data for the past 86 to 112 yr. Comparative analysis of the temperature data of six nonindustrial stations has also been done. The long-term change in the temperature has been evaluated by linear trend. Calcutta, Bombay and Bangalore have shown significant warning trend, while Delhi has shown a cooling trend. The trends at Madras and Pune are not significant. The nonindustrial stations did not show significant trends. In general, there was either a cooling tendency or cessation of warming, after the late 1950s at most of the industrial cities.     

Estimating the potential predictability of Australian surface maximum and minimum temperature

A study is made of the potential predictability of seasonal means in Australian surface maximum and minimum temperature using monthly data from December 1950 to November 2000. Because the usual assumption of stationarity cannot be applied to the observations at all stations and for all seasons, a modification to an existing methodology is proposed. Here, we show that, to a first order, monthly mean variances within a season can be modeled by a linear relationship, and inter-monthly correlations can be assumed to be stationary. The intraseasonal component of variability can then be estimated using monthly data. Removing the intraseasonal variance from the total interannual variance allows an estimate of the potential predictability to be made. Surface maximum and minimum temperature has high potential predictability over most of northern Australia in the four main seasons. However, there is high potential predictability only in some of the four seasons for the centre and south of Australia. Surface minimum temperature is generally more potentially predictable than surface maximum temperature. The spatial and temporal patterns of potential predictability are generally consistent with published patterns of hindcast skill from a statistical forecast scheme. A comparison between the intraseasonal variance of Australian surface maximum and minimum temperature estimated using the stationary variance assumption and the linear assumptions showed qualitatively and quantitatively similar patterns of distribution.     

Are response function representations of the global carbon cycle ever interpretable?

Response function models are often used to represent the behaviour of complex, high order global carbon cycle (GCC) and climate models in applications which require short model run times. Although apparently black-box, these response function models need not necessarily be entirely opaque, but instead may also convey useful insights into the properties of the parent model or process. By exploiting a transfer function (TF) framework to analyse the Lenton GCC model, this paper attempts to demonstrate that response function representations of GCC models can sometimes also provide structural information on the parent model from which they are identified and calibrated. We take a fifth-order TF identified from the impulse response of the Lenton model atmospheric burden, and decompose this to show how it can be re-expresses in a generic five-box form in sympathy with the structure of the parent model.     

The reliability of global and hemispheric surface temperature records

The purpose of this review article is to discuss the development and associated estimation of uncertainties in the global and hemispheric surface temperature records. The review begins by detailing the groups that produce surface temperature datasets. After discussing the reasons for similarities and differences between the various products, the main issues that must be addressed when deriving accurate estimates, particularly for hemispheric and global averages, are then considered.These issues are discussed in the order of their importance for temperature records at these spatial scales: biases in SST data,particularly before the 1940s; the exposure of land-based thermometers before the development of louvred screens in the late 19th century; and urbanization effects in some regions in recent decades. The homogeneity of land-based records is also discussed; however, at these large scales it is relatively unimportant. The article concludes by illustrating hemispheric and global temperature records from the four groups that produce series in near-real time.     

Long-term variability of sea surface temperature in Taiwan Strait

Long-term variability of sea surface temperature (SST) in the Taiwan Strait was studied from the U.K. Met Office Hadley Centre climatological data set HadISST1. In 1957–2011, three epochs were identified. The first epoch of cooling SST lasted through 1976. The regime shift of 1976–1977 led to an extremely rapid warming of 2.1 °C in 22 years. Another regime shift occurred in 1998–1999, resulting in a 1.0 °C cooling by 2011. The cross-frontal gradient between the China Coastal Current and offshore Taiwan Strait waters has abruptly decreased in 1992 and remained low through 2011. The long-term warming of SST increased towards the East China Sea, where the SST warming in 1957–2011 was about three times that in the South China Sea. The long-term warming was strongly enhanced in winter, with the maximum warming of 3.8 °C in February. The wintertime amplification of long-term warming has resulted in a decrease of the north–south SST range from 5 to 4 °C and a decrease in the amplitude of seasonal cycle of SST from 11 to 8 °C.     

Modes of variability of global sea surface temperature,free atmosphere temperature and oceanic surface energy flux

Monthly mean sea surface temperature (SST), free air temperature from satellite microwave sounding units (MSU) and oceanic surface energy fluxes are subjected to empirical orthogonal function (EOF) analysis for a common decade to investigate the physical relationships involved. The first seasonal modes of surface solar energy flux and SST show similar inter-hemispheric patterns with an annual cycle. Solar flux appears to control this pattern of SST. The first seasonal mode of MSU is similar with, additionally, land-sea differences; MSU is apparently partly controlled by absorption of solar near-infrared radiation and partly by sensible heat from the land surface. The second and third seasonal eigenvector of SST and solar flux exhibit semi-annual oscillations associated with a pattern of cloudiness in the subtropics accompanying the translation of the Hadley cell rising motion between the hemispheres. The second seasonal mode of MSU is dominated by an El Niño signal. The first nonseasonal EOFs of SST and solar flux exhibit El Niño characteristics with the solar pattern being governed by west-to-east translation of a Walker cell type pattern. The first non-seasonal EOF of MSU shows a tropical strip pattern for the El Niño mode, which is well correlated with the latent heat fluxes in the tropical east Pacific but not in the tropical west Pacific. Two possible explanations are: an increase in subsidence throughout the tropical strip driven by extra evaporation in the tropical east Pacific and consequent additional latent heat liberation; a decrease of meridional heat flux out of the tropics.     

Tropical soils could dominate the short-term carbon cycle feedbacks to increased global temperatures

Results of a simple model of the effects of temperature on net ecosystem production call into question the argument that the large stocks of soil carbon and greater projected warming in the boreal and tu ndra regions of the world willlead to rapid efflux of carbon from these biomes to the atmosphere. We show that low rates of carbon turnover in these regions and a relatively greater response of net primary production to changes in temperature may lead to carbon storage over some limited range of warming. In contrast, the high rates of soil respiration found in tropical ecosystems are highly sensitive to small changes in temperature, so that despite the less pronounced warming expected in equatorial regions, tropical soils are likely to release relatively large amounts of carbon to the atmosphere. Results for high-latitude biomes are highly sensitive to parameter values used, while the net efflux of carbon from the tropics appears robust.     

An updated evaluation of the global mean land surface air temperature and surface temperature trends based on CLSAT and CMST

Climate Dynamics - Past versions of global surface temperature (ST) datasets have been shown to have underestimated the recent warming trend over 1998–2012. This study uses a newly updated...     

Is Granger causality analysis appropriate to investigate the relationship between atmospheric concentration of carbon dioxide and global surface air temperature?

Summary Many time series based studies use Granger causality analysis in order to investigate the connection between atmospheric carbon-dioxide concentrations and global mean temperature. This note re-examines the causal relationship between these variables and shows the inappropriateness of the Granger test to the problem under investigation.     

Long-term variations in surface air pressure and surface air temperature in the Northern Hemisphere mid-latitudes

The spatiotemporal variability of surface air pressure and surface air temperature in the Northern Hemisphere troposphere in 1990-2014 is described. In 2005 the low-frequency component (LFC) of average air temperature in January averaged over the latitude zone of 32.5°-67.5° N has stopped its increase that lasted for 35 years (from 1970). The LFC of air temperature in July has continued growing since 1975 (for 39 years). The anomalies of air pressure and air temperature for thirty-year periods and the dynamics of LFC of air temperature and air pressure in the atmospheric centers of action are analyzed.     

Long-term trend in potential vorticity intrusion events over the Pacific Ocean: Role of global mean temperature rise

In this study, we examine a long-term increasing trend in subtropical potential vorticity (PV) intrusion events over the Pacific Ocean in relation to the global mean temperature rise, based on multiple reanalysis datasets. The frequency of the PV intrusions is closely related to the upper-tropospheric equatorial westerly duct and the subtropical jet (STJ). An overall strengthening of the westerly duct and weakening of the STJ are found to be driven by the warming-induced strengthening of Walker circulation and regional changes in Hadley circulation on multi-decadal timescale, leading to an increase in the PV intrusion frequency over the tropics. The results are robust in all datasets. The multi-decadal strengthening in the Pacific Walker circulation is consistent with the global mean temperature rise. In this way, the PV intrusions are correlated with the warming related global mean temperuate rise. When the interannual variability of ENSO is removed from the intrusion time series, the long-term trend in PV intrusions due to external forcing associated with anthropogenic warming (global mean temperature rise) becomes clearer. The link between the global mean temperature rise and intrusion frequency is further verified by performing a correlation analysis between the two. The significant (> 95%) correlation coefficient is 0.85, 0.94, 0.84, 0.83, and 0.84 for ERA-40, ERA-Interim, NCEP-NCAR, JRA-55, and JRA-25, respectively. This unequivocally indicates that the global mean temperature rise can explain around 69%–88% of the variance related to the long-term increase in PV intrusion frequency over the Pacific Ocean.     

Long-term changes in the number and temperature of hot days in Georgia under global warming

Variations in the number of hot days, their frequency, intensity, and duration in Georgia are studied using observational data from 50 weather stations for the period of 1936-2013. The periods of the onset of hot days in the year and their maximum intensity in different physiographic conditions are identified. The zoning of Georgia was carried out according to the rate of changes in the number of hot days. The results enhance the understanding of climate change in Georgia under global warming conditions.     

A simulation study for the global carbon cycle,including man's impact on the biosphere

The simulation model accounts for four major compartments in the global carbon cycle: atmosphere, ocean, terrestrial biosphere and fossil carbon reservoir. The ocean is further compartmentalized into a high and a low latitude surface layer, and into 10 deep sea strata. The oceanic carbon fluxes are caused by massflow of descending and upwelling water, by precipitation of organic material and by diffusion exchange.The biosphere is horizontally subdivided into six ecosystems and vertically into leaves, branches, stemwood, roots, litter, young humus and stable soil carbon. Deforestation, slash and burn agriculture, rangeland burning and shifts in land use have been included. The atmosphere is treated as one well mixed reservoir. Fossil fuel consumption is simulated with historic data, and with IIASA scenario's for the future. Using the low IIASA scenario an atmospheric CO₂ concentration of 431 ppmv is simulated for 2030 AD. A sensitivity analysis shows the importance of different parameters and of human behaviour. Notwithstanding the large size of the biosphere fluxes, the atmospheric CO₂ concentration in the next century will be predominantly determined by the growth rate of fossil fuel consumption.