4,734 research outputs found
On the Sherlocks, Jane Coleman and County Kildare in the Eighteen Forties
No full textIn the late 1980s and early 1990s the author acquired about 30,000 letters written mainly in the 1840s. These pertained to estates throughout Ireland managed by the firm of James Robert Stewart and Joseph Kincaid, hereafter denoted SK. Until the letters – called the SK correspondence in what follows – became the author’s property, they had not seen light of day since the 1840s. Addressed mainly to the firm’s office in Dublin, they were written by landlords, tenants, the partners in SK, local agents, etc. After about 200 years in operation as a land agency, the firm in which members of the Stewart family were the principal partners – Messrs J. R. Stewart & Son(s) from the mid- 1880s onwards – ceased operations in the mid-1980s. Since 1994 the author has been researching the SK correspondence of the 1840s. It gives many new insights into economic and social conditions in Ireland during the decade of the great famine, and into the operation of Ireland’s most important land agency during those years. It is intended ultimately to publish details on several of the estates managed by SK in a study more comprehensive than the present article, in book form. The proposed title is Landlords, tenants, famine: business of an Irish land agency in the 1840s, a draft of which has now been completed. A majority of the letters in that study are on themes some of which one might expect - rents, distraint (seizure of assets in lieu of rent); ‘voluntary’ surrender of land in return for ‘compensation’ upon quitting quietly; formal ejectment (a matter of last resort on estates managed by SK); landlordassisted emigration (on a scale much more extensive than most historians of Ireland in the 1840s appear to believe); petitions from tenants; complaints by tenants, both about other tenants and about local agents; landlord-financed and other relief of distress both before and during the great famine; major works of improvement (on almost all of the estates managed by SK which have been investigated in detail in the draft book); applications by SK, on behalf of landlords, for government loans to finance improvements; recommendations of agricultural advisers hired by SK, etc. Thus, most of the SK correspondence is about aspects of estate management. But the firm of SK was not only a manager of land. The correspondence reveals only two estates in Kildare, each of them relatively small, managed by SK in the 1840s. These were the lands of the Sherlocks near Naas and of Jane Coleman in the Kilcullen district. The correspondence on these properties differs substantively from most of those discussed in detail in the draft of Landlords, tenants, famine: first, it is relatively small in quantity, and secondly, it contains relatively little on the core aspects of estate management indicated above. Much of that on the Sherlocks focuses on misfortunes among family members, while the correspondence on Jane Coleman highlights the benevolence of that proprietor.
Spatiotemporal patterns of changes in maximum and minimum temperatures in multi-model simulations
No full textThis paper analyzes and attributes spatial and temporal patterns of changes in the diurnal cycle of land surface air temperature in 20 simulations from 11 global coupled atmosphere-ocean general circulation models during the 20th century and the 21st century under the SRES A1B scenario. Most of the warming in the maximum (T-max) and minimum (T-min) temperatures from 1900 to 2099 is attributed to enhanced surface downward longwave radiation (DLW), while changes in surface downward shortwave radiation (DSW) and cloud cover mainly contribute to the simulated decrease in the diurnal temperature range (DTR). Although the simulated DTR decreases are much smaller than the observed during the 20th century, the models unanimously predict substantial warming in both Tmax and Tmin and decreases in DTR, especially in high latitudes during the 21st century, in response to enhanced global-scale anthropogenic forcings (particularly greenhouse effects of atmospheric water vapor and in part aerosol radiative cooling in the tropics) and increased cloudiness in high latitudes. Citation: Zhou, L., R. E. Dickinson, P. Dirmeyer, A. Dai, and S.-K. Min (2009), Spatiotemporal patterns of changes in maximum and minimum temperatures in multi-model simulations, Geophys. Res. Lett., 36, L02702, doi: 10.1029/2008GL036141.X112522sciescopu
A Bayesian assessment of climate change using multimodel ensembles. Part II: regional and seasonal mean surface temperatures
No full textA Bayesian approach is applied to the observed regional and seasonal surface air temperature ( SAT) changes using single- model ensembles ( SMEs) with the ECHO- G model and multimodel ensembles ( MMEs) of the Intergovernmental Panel on Climate Change ( IPCC) Fourth Assessment Report ( AR4) simulations. Bayesian decision classifies observations into the most probable scenario out of six available scenarios: control ( CTL), natural forcing ( N), anthropogenic forcing ( ANTHRO), greenhouse gas ( G), sulfate aerosols ( S), and natural plus anthropogenic forcing ( ALL). Space - time vectors of the detection variable are constructed for six continental regions ( North America, South America, Asia, Africa, Australia, and Europe) by combining temporal components of SATs ( expressed as Legendre coefficients) from two or three subregions of each continental region. Bayesian decision results show that over most of the regions observed SATs are classified into ALL or ANTHRO scenarios for the whole twentieth century and its second half. Natural forcing and ALL scenarios are decided during the first half of the twentieth century, but only in the low- latitude region ( Africa and South America), which might be related to response patterns to solar forcing. Overall seasonal decisions follow annual results, but there are notable seasonal dependences that differ between regions. A comparison of SME and MME results demonstrates that the Bayesian decisions for regional- scale SATs are largely robust to intermodel uncertainties as well as prior probability and temporal scales, as found in the global results.X111921sciescopu
A Bayesian approach to climate model evaluation and multi-model averaging with an application to global mean surface temperatures from IPCC AR4 coupled climate models
No full textA Bayesian approach is introduced to model evaluation and multi-model averaging with a systematic consideration of model uncertainty, and its application to global mean surface air temperature (SAT) changes is shown from multi-AOGCM ensembles of IPCC AR4 simulations. The Bayes factor or likelihood ratio of each model to the reference model (where mean is identical to the observation) provides a skill ranging from 0 to 1. Four categories of model skill are derived on the basis of the previous studies. Legendre series expansions are used to get a temporally refined model evaluation, which allow efficient analyses of time mean (scale) and linear trend. Application results show that all AOGCMs with natural plus anthropogenic forcing can simulate well the scale and trend of observed global mean SAT changes over the 20th century and its first and second halves. However, more than 50% of the models with anthropogenic-only forcing cannot reproduce the observed warming reasonably. This indicates the important role of natural forcing although other factors like different climate sensitivity, forcing uncertainty, and a climate drift might be responsible for the discrepancy in anthropogenic-only models. Besides, Bayesian and conventional skill comparisons demonstrate that a skill-weighted average with the Bayes factors (Bayesian model averaging, BMA) overwhelms the arithmetic ensemble mean and three other weighted averages based on conventional statistics, illuminating future applicability of BMA to climate predictions.X115952sciescopu
A Hierarchical evaluation of IPCC AR4 coupled climate models with systematic consideration of model uncertainties
No full textThe capability of reproducing observed surface air temperature (SAT) changes for the twentieth century is assessed using 22 multi-models which contribute to the Intergovernmental Panel on Climate Change Fourth Assessment Report. A Bayesian method is utilized for model evaluation by which model uncertainties are considered systematically. We provide a hierarchical analysis for global to sub-continental regions with two settings. First, regions of different size are evaluated separately at global, hemispheric, continental, and sub-continental scales. Second, the global SAT trend patterns are evaluated with gradual refinement of horizontal scales (higher dimensional analysis). Results show that models with natural plus anthropogenic forcing (MME ALL) generally exhibit better skill than models with anthropogenic only forcing (MME_ANTH) at all spatial scales for different trend periods (entire twentieth century and its first and second halves). This confirms previous studies that suggest the important role of natural forcing. For the second half of the century, we found that MME_ANTH performs well compared to MME _ ALL except for a few models with overestimated warming. This indicates not only major contributions of anthropogenic forcing over that period but also the applicability of both MMEs to observationally constrained future predictions of climate changes. In addition, the skill-weighted averages with the Bayes factors [Bayesian model averaging (BMA)] show a general superiority over other error-based weighted averaging methods, suggesting a potential advantage of BMA for climate change predictions.X111514sciescopu
A Bayesian assessment of climate change using multimodel ensembles. Part I: Global mean surface temperature
No full textA Bayesian approach is applied to the observed global surface air temperature ( SAT) changes using multimodel ensembles (MMEs) of the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) simulations and single-model ensembles (SMEs) with the ECHO-G coupled climate model. A Bayesian decision method is used as a tool for classifying observations into given scenarios ( or hypotheses). The prior probability of the scenarios, which represents a degree of subjective belief in the scenarios, is changed into the posterior probability through the likelihood where observations enter, and the posterior is used as a decision function. In the identical prior case the Bayes factor ( or likelihood ratio) becomes a decision function and provides observational evidence for each scenario against a predefined reference scenario. Four scenarios are used to explain observed SAT changes: "CTL" ( control or no change), "Nat" ( natural forcing induced change), "GHG" ( greenhouse gas - induced change), and "All" ( natural plus anthropogenic forcing - induced change). Observed and simulated global mean SATs are decomposed into temporal components of overall mean, linear trend, and decadal variabilities through Legendre series expansions, coefficients of which are used as detection variables. Parameters ( means and covariance matrices) needed to define the four scenarios are estimated from SMEs or MMEs. Taking the CTL scenario as reference one, application results for global mean SAT changes for the whole twentieth century ( 1900 - 99) show "decisive" evidence ( logarithm of Bayes factor > 5) for the All scenario only. While "strong" evidence ( log of Bayes factor > 2.5) for both the Nat and All scenarios are found in SAT changes for the first half ( 1900 - 49), there is decisive evidence for the All scenario for SAT changes in the second half ( 1950 - 99), supporting previous results. It is demonstrated that the Bayesian decision results for global mean SATs are largely insensitive to both intermodel uncertainties and prior probabilities.X113734sciescopu
Human influence on Arctic sea ice detectable from early 1990s onwards
No full textHuman influence has previously been identified in the observed loss of Arctic sea ice, but this hypothesis has not yet been tested with a formal optimal detection approach. By comparing observed and multi-model simulated changes in Arctic sea ice extent during 1953-2006 using an optimal fingerprinting method, we find that the anthropogenic signal first emerged in the early 1990s, indicating that human influence could have been detected even prior to the recent dramatic sea ice decline. The anthropogenic signal is also detectable for individual months from May to December, suggesting that human influence, strongest in late summer, now also extends into colder seasons. Citation: Min, S.-K., X. Zhang, F. W. Zwiers, and T. Agnew (2008), Human influence on Arctic sea ice detectable from early 1990s onwards, Geophys. Res. Lett., 35, L21701, doi:10.1029/2008GL035725.X114648sciescopu
Multi-model attribution of the Southern Hemisphere Hadley cell widening: Major role of ozone depletion
No full textIt has been suggested that the Hadley cell has been widening during the past three decades in both hemispheres, but attribution of its cause(s) remains challenging. By applying an optimal fingerprinting technique to 7 modern reanalyses and 49 coupled climate models participating in the CMIP3 and CMIP5, here we detect an influence of human-induced stratospheric ozone depletion on the observed expansion of the Hadley cell in the Southern Hemisphere (SH) summer. The detected signal is found to be separable from other external forcings that include greenhouse gases (GHGs), confirming a dominant role of stratospheric ozone in the SH summer climate change. Our results are largely insensitive to observational and model uncertainties, providing additional evidence for a human contribution to the atmospheric circulation changes.X113326sciescopu
The degree of respiratory depression according to the effect-site concentration in remimazolam target-controlled infusion : A randomised controlled trial
No full textBACKGROUND Remimazolam is not only associated with a lower incidence of respiratory depression than propofol but also in itself has the risk of respiratory depression. OBJECTIVE We investigated respiratory depression following remimazolam infusion, targeting different effect-site concentrations using target-controlled infusion. DESIGN A prospective, double-blind, randomised controlled study. SETTING Tertiary hospital, Suwon, South Korea, from April 2022 to November 2022. PARTICIPANTS One hundred and seven patients scheduled for general anaesthesia were randomised into three groups targeting remimazolam effect-site concentrations of 500 (RMZ-500) (n = 36), 1000 (RMZ-1000) (n = 35) and 1500 ng ml-1 (RMZ-1500) (n = 36). INTERVENTIONS Remimazolam was solely infused for 10 min according to target effect-site concentrations. According to the degree of SpO2 decrease, oxygen desaturations were managed with the following respiratory supports: jaw-thrust for SpO2 less than 97%, 100% oxygen delivery for SpO2 less than 93% and assisted ventilation for SpO2 less than 90%. MAIN OUTCOME MEASURES The incidence of each respiratory support, along with respiratory variables (at baseline, 5 min and 10 min after remimazolam infusion) and loss of consciousness were observed for 10 min after remimazolam target-controlled infusion. RESULTS Both RMZ-1000 and RMZ-1500 required more frequent respiratory support than RMZ-500 (both P < 0.001), with nearly identical frequencies between RMZ-1000 and RMZ-1500. In terms of respiratory support, the incidence of assisted ventilation was significantly lower in RMZ-500 (2.8%) than RMZ-1000 (48.6%) and RMZ-1500 (50%) (P < 0.001). RMZ-1000 and RMZ-1500 achieved loss of consciousness in all patients; RMZ-500 only achieved loss of consciousness in 86.1% of patients (P = 0.010). In patients who maintained spontaneous respiration, tidal volume decreased by 41 to 48% and respiratory rate increased by 118 to 158% at 5 and 10 min, significantly compared to baseline in all groups (P < 0.001). CONCLUSIONS Remimazolam infusion, like that of other benzodiazepines, led to respiratory depression, which was more prominent at higher target effect-site concentrations. Therefore, appropriate countermeasures should be developed to prevent oxygen desaturation
NLINLS: a Differential Evolution based nonlinear least squares Fortran 77 program
No full textThis paper provides the list of Fortran 77 codes of nonlinear least squares using Differential Evolution as the minimizer algorithm. It has been tested on a number of difficult nonlinear least squares problems (taken from NIST, USA including CPC-X Software challenge problems). Help on how to use the program also is provided.Nonlinear least squares; Differential Evolution; Fortran 77
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