8 resultados para temperature-programmed techniques

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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MIPAS observations of temperature, water vapor, and ozone in October 2009 as derived with the scientific level-2 processor run by Karlsruhe Institute of Technology (KIT), Institute for Meteorology and Climate Research (IMK) and CSIC, Instituto de Astrofísica de Andalucía (IAA) and retrieved from version 4.67 level-1b data have been compared to co-located field campaign observations obtained during the MOHAVE-2009 campaign at the Table Mountain Facility near Pasadena, California in October 2009. The MIPAS measurements were validated regarding any potential biases of the profiles, and with respect to their precision estimates. The MOHAVE-2009 measurement campaign provided measurements of atmospheric profiles of temperature, water vapor/relative humidity, and ozone from the ground to the mesosphere by a suite of instruments including radiosondes, ozonesondes, frost point hygrometers, lidars, microwave radiometers and Fourier transform infra-red (FTIR) spectrometers. For MIPAS temperatures (version V4O_T_204), no significant bias was detected in the middle stratosphere; between 22 km and the tropopause MIPAS temperatures were found to be biased low by up to 2 K, while below the tropopause, they were found to be too high by the same amount. These findings confirm earlier comparisons of MIPAS temperatures to ECMWF data which revealed similar differences. Above 12 km up to 45 km, MIPAS water vapor (version V4O_H2O_203) is well within 10% of the data of all correlative instruments. The well-known dry bias of MIPAS water vapor above 50 km due to neglect of non-LTE effects in the current retrievals has been confirmed. Some instruments indicate that MIPAS water vapor might be biased high by 20 to 40% around 10 km (or 5 km below the tropopause), but a consistent picture from all comparisons could not be derived. MIPAS ozone (version V4O_O3_202) has a high bias of up to +0.9 ppmv around 37 km which is due to a non-identified continuum like radiance contribution. No further significant biases have been detected. Cross-comparison to co-located observations of other satellite instruments (Aura/MLS, ACE-FTS, AIRS) is provided as well.

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This paper presents a comparison of principal component (PC) regression and regularized expectation maximization (RegEM) to reconstruct European summer and winter surface air temperature over the past millennium. Reconstruction is performed within a surrogate climate using the National Center for Atmospheric Research (NCAR) Climate System Model (CSM) 1.4 and the climate model ECHO-G 4, assuming different white and red noise scenarios to define the distortion of pseudoproxy series. We show how sensitivity tests lead to valuable “a priori” information that provides a basis for improving real world proxy reconstructions. Our results emphasize the need to carefully test and evaluate reconstruction techniques with respect to the temporal resolution and the spatial scale they are applied to. Furthermore, we demonstrate that uncertainties inherent to the predictand and predictor data have to be more rigorously taken into account. The comparison of the two statistical techniques, in the specific experimental setting presented here, indicates that more skilful results are achieved with RegEM as low frequency variability is better preserved. We further detect seasonal differences in reconstruction skill for the continental scale, as e.g. the target temperature average is more adequately reconstructed for summer than for winter. For the specific predictor network given in this paper, both techniques underestimate the target temperature variations to an increasing extent as more noise is added to the signal, albeit RegEM less than with PC regression. We conclude that climate field reconstruction techniques can be improved and need to be further optimized in future applications.

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Previous studies have either exclusively used annual tree-ring data or have combined tree-ring series with other, lower temporal resolution proxy series. Both approaches can lead to significant uncertainties, as tree-rings may underestimate the amplitude of past temperature variations, and the validity of non-annual records cannot be clearly assessed. In this study, we assembled 45 published Northern Hemisphere (NH) temperature proxy records covering the past millennium, each of which satisfied 3 essential criteria: the series must be of annual resolution, span at least a thousand years, and represent an explicit temperature signal. Suitable climate archives included ice cores, varved lake sediments, tree-rings and speleothems. We reconstructed the average annual land temperature series for the NH over the last millennium by applying 3 different reconstruction techniques: (1) principal components (PC) plus second-order autoregressive model (AR2), (2) composite plus scale (CPS) and (3) regularized errors-in-variables approach (EIV). Our reconstruction is in excellent agreement with 6 climate model simulations (including the first 5 models derived from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and an earth system model of intermediate complexity (LOVECLIM), showing similar temperatures at multi-decadal timescales; however, all simulations appear to underestimate the temperature during the Medieval Warm Period (MWP). A comparison with other NH reconstructions shows that our results are consistent with earlier studies. These results indicate that well-validated annual proxy series should be used to minimize proxy-based artifacts, and that these proxy series contain sufficient information to reconstruct the low-frequency climate variability over the past millennium.

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TEMPERA (TEMPERature RAdiometer) is a new ground-based radiometer which measures in a frequency range from 51–57 GHz radiation emitted by the atmosphere. With this instrument it is possible to measure temperature profiles from ground to about 50 km. This is the first ground-based instrument with the capability to retrieve temperature profiles simultaneously for the troposphere and stratosphere. The measurement is done with a filterbank in combination with a digital fast Fourier transform spectrometer. A hot load and a noise diode are used as stable calibration sources. The optics consist of an off-axis parabolic mirror to collect the sky radiation. Due to the Zeeman effect on the emission lines used, the maximum height for the temperature retrieval is about 50 km. The effect is apparent in the measured spectra. The performance of TEMPERA is validated by comparison with nearby radiosonde and satellite data from the Microwave Limb Sounder on the Aura satellite. In this paper we present the design and measurement method of the instrument followed by a description of the retrieval method, together with a validation of TEMPERA data over its first year, 2012.

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Varved lake sediments are excellent natural archives providing quantitative insights into climatic and environmental changes at very high resolution and chronological accuracy. However, due to the multitude of responses within lake ecosystems it is often difficult to understand how climate variability interacts with other environmental pressures such as eutrophication, and to attribute observed changes to specific causes. This is particularly challenging during the past 100 years when multiple strong trends are superposed. Here we present a high-resolution multi-proxy record of sedimentary pigments and other biogeochemical data from the varved sediments of Lake Żabińskie (Masurian Lake District, north-eastern Poland, 54°N–22°E, 120 m a.s.l.) spanning AD 1907 to 2008. Lake Żabińskie exhibits biogeochemical varves with highly organic late summer and winter layers separated by white layers of endogenous calcite precipitated in early summer. The aim of our study is to investigate whether climate-driven changes and anthropogenic changes can be separated in a multi-proxy sediment data set, and to explore which sediment proxies are potentially suitable for long quantitative climate reconstructions. We also test if convoluted analytical techniques (e.g. HPLC) can be substituted by rapid scanning techniques (visible reflectance spectroscopy VIS-RS; 380–730 nm). We used principal component analysis and cluster analysis to show that the recent eutrophication of Lake Żabińskie can be discriminated from climate-driven changes for the period AD 1907–2008. The eutrophication signal (PC1 = 46.4%; TOC, TN, TS, Phe-b, high TC/CD ratios total carotenoids/chlorophyll-a derivatives) is mainly expressed as increasing aquatic primary production, increasing hypolimnetic anoxia and a change in the algal community from green algae to blue-green algae. The proxies diagnostic for eutrophication show a smooth positive trend between 1907 and ca 1980 followed by a very rapid increase from ca. 1980 ± 2 onwards. We demonstrate that PC2 (24.4%, Chl-a-related pigments) is not affected by the eutrophication signal, but instead is sensitive to spring (MAM) temperature (r = 0.63, pcorr < 0.05, RMSEP = 0.56 °C; 5-yr filtered). Limnological monitoring data (2011–2013) support this finding. We also demonstrate that scanning visible reflectance spectroscopy (VIS-RS) data can be calibrated to HPLC-measured chloropigment data and be used to infer concentrations of sedimentary Chl-a derivatives {pheophytin a + pyropheophytin a}. This offers the possibility for very high-resolution (multi)millennial-long paleoenvironmental reconstructions.

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This study aims at assessing the skill of several climate field reconstruction techniques (CFR) to reconstruct past precipitation over continental Europe and the Mediterranean at seasonal time scales over the last two millennia from proxy records. A number of pseudoproxy experiments are performed within the virtual reality ofa regional paleoclimate simulation at 45 km resolution to analyse different aspects of reconstruction skill. Canonical Correlation Analysis (CCA), two versions of an Analog Method (AM) and Bayesian hierarchical modeling (BHM) are applied to reconstruct precipitation from a synthetic network of pseudoproxies that are contaminated with various types of noise. The skill of the derived reconstructions is assessed through comparison with precipitation simulated by the regional climate model. Unlike BHM, CCA systematically underestimates the variance. The AM can be adjusted to overcome this shortcoming, presenting an intermediate behaviour between the two aforementioned techniques. However, a trade-off between reconstruction-target correlations and reconstructed variance is the drawback of all CFR techniques. CCA (BHM) presents the largest (lowest) skill in preserving the temporal evolution, whereas the AM can be tuned to reproduce better correlation at the expense of losing variance. While BHM has been shown to perform well for temperatures, it relies heavily on prescribed spatial correlation lengths. While this assumption is valid for temperature, it is hardly warranted for precipitation. In general, none of the methods outperforms the other. All experiments agree that a dense and regularly distributed proxy network is required to reconstruct precipitation accurately, reflecting its high spatial and temporal variability. This is especially true in summer, when a specifically short de-correlation distance from the proxy location is caused by localised summertime convective precipitation events.