992 resultados para Air temperature


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"Greenhouse heating" of the atmosphere due to trace gases seems apparent to those who model with averages but not to those who examine individual temperature records. Temperature trends are on the minds of all those concerned with the environmental influence of the increasing human population. The big problem remains - where and how do we take the Earth's temperature? ... In California, there are 112 temperature records for 1910 to 1989; all of them were used here to examine trends in annual temperature.

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The AMSR-E satellite data and in-situ data were applied to retrieve sea surface air temperature (Ta) over the Southern Ocean. The in-situ data were obtained from the 24~(th) -26~(th) Chinese Antarctic Expeditions during 2008-2010. First, Ta was used to analyze the relativity with the bright temperature (Tb) from the twelve channels of AMSR-E, and no high relativity was found between Ta and Tb from any of the channels. The highest relativity was 0.38 (with 23.8 GHz). The dataset for the modeling was obtained by using in-situ data to match up with Tb, and two methods were applied to build the retrieval model. In multi-parameters regression method, the Tbs from 12 channels were used to the model and the region was divided into two parts according to the latitude of 50°S. The retrieval results were compared with the in-situ data. The Root Mean Square Error (RMS) and relativity of high latitude zone were 0.96℃and 0.93, respectively. And those of low latitude zone were 1.29 ℃ and 0.96, respectively. Artificial neural network (ANN) method was applied to retrieve Ta.The RMS and relativity were 1.26 ℃ and 0.98, respectively.

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We present chironomid-based temperature reconstructions from lake sediments deposited between ca 26,600 cal yr BP and 24,500 cal yr BP from Lyndon Stream, South Island, New Zealand. Summer (February mean) temperatures averaged 1 1C cooler, with a maximum inferred cooling of 3.7 1C. These estimates corroborate macrofossil and beetle-based temperature inferences from the same site and suggest climate amelioration (an interstadial) at this time. Other records from the New Zealand region also show a large degree of variability during the late Otiran glacial sequence (34,000–18,000 cal yr BP) including a phase of warming at the MIS 2/3 transition and a maximum cooling that did not occur until the global LGM (ca 20,000 cal yr BP). The very moderate cooling identified here at the MIS 2/3 transition confirms and enhances the long-standing discrepancy in New Zealand records between pollen and other proxies. Low abundances (o20%) of canopy tree pollen in records from late MIS 3 to the end of MIS 2 cannot be explained by the minor (o5 1C) cooling inferred from this and other studies unless other environmental parameters are considered. Further work is required to address this critical issue.

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The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

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The application of the Radial Basis Function (RBF) Neural Network (NN) to greenhouse inside air temperature modelling has been previously investigated (Ferreira et al., 2000a). In those studies, the inside air temperature is modelled as a function of the inside relative humidity and of the outside temperature and solar radiation. A second-order model structure previously selected (Cunha et al., 1996) in the context of dynamic temperature models identification, is used.

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We have previously placed the solar contribution to recent global warming in context using observations and without recourse to climate models. It was shown that all solar forcings of climate have declined since 1987. The present paper extends that analysis to include the effects of the various time constants with which the Earth’s climate system might react to solar forcing. The solar input waveform over the past 100 years is defined using observed and inferred galactic cosmic ray fluxes, valid for either a direct effect of cosmic rays on climate or an effect via their known correlation with total solar irradiance (TSI), or for a combination of the two. The implications, and the relative merits, of the various TSI composite data series are discussed and independent tests reveal that the PMOD composite used in our previous paper is the most realistic. Use of the ACRIM composite, which shows a rise in TSI over recent decades, is shown to be inconsistent with most published evidence for solar influences on pre-industrial climate. The conclusions of our previous paper, that solar forcing has declined over the past 20 years while surface air temperatures have continued to rise, are shown to apply for the full range of potential time constants for the climate response to the variations in the solar forcings.

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Time series of global and regional mean Surface Air Temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies and Simple Kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, Root Mean Square Errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Non-interpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979-2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.

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We present ocean model sensitivity experiments aimed at separating the influence of the projected changes in the “thermal” (near-surface air temperature) and “wind” (near-surface winds) forcing on the patterns of sea level and ocean heat content. In the North Atlantic, the distribution of sea level change is more due to the “thermal” forcing, whereas it is more due to the “wind” forcing in the North Pacific; in the Southern Ocean, the “thermal” and “wind” forcing have a comparable influence. In the ocean adjacent to Antarctica the “thermal” forcing leads to an inflow of warmer waters on the continental shelves, which is somewhat attenuated by the “wind” forcing. The structure of the vertically integrated heat uptake is set by different processes at low and high latitudes: at low latitudes it is dominated by the heat transport convergence, whereas at high latitudes it represents a small residual of changes in the surface flux and advection of heat. The structure of the horizontally integrated heat content tendency is set by the increase of downward heat flux by the mean circulation and comparable decrease of upward heat flux by the subgrid-scale processes; the upward eddy heat flux decreases and increases by almost the same magnitude in response to, respectively, the “thermal” and “wind” forcing. Regionally, the surface heat loss and deep convection weaken in the Labrador Sea, but intensify in the Greenland Sea in the region of sea ice retreat. The enhanced heat flux anomaly in the subpolar Atlantic is mainly caused by the “thermal” forcing.

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Exhaled air temperature (T exh) has a paramount effect on respiratory water loss during flight. For migratory birds, low T exh potentially reduces water loss and increases flight range. However, only three studies provide empirical data on T exh during flight. The aim of this study was to record T exh of birds during rest and flight at a range of controlled ambient temperatures (T amb). One wigeon and two teal flew a total of 20 times in a wind tunnel at T amb ranging from 1° to 24°C. T exh during flight did not differ between the two species and was strongly correlated with T amb (T exh=1.036 T amb + 13.426; R2=0.58). In addition, body temperature had a weak positive effect on T exh. At a given T amb, T exh was about 5°C higher during flight than at rest.

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