A multiple Linear Regression Model to predict indoor temperature trend in historic buildings for book conservation: the case study of “Sala del Dottorato” in Palazzo Murena, Italy

The indoor climate of historic buildings is governed by the desire to preserve them, their interiors and to ensure human comfort. For preservation of cultural heritage and libraries, relative humidity and temperature are very important parameters, including their amplitudes and changes rate in time. In the present study an experimental campaign of thermo-hygrometric parameters inside of “Sala del Dottorato”, located in Palazzo Murena (Perugia), is carried out. In this room a great number of rare and ancient books are preserved. The paper deals with the study and the evaluation of the correlation between outdoor and indoor microclimate conditions in the room, to ensure the proper conservation of the books; it is aimed at understanding how the two parameters follow outdoor variations and how the hygrothermal inertia of the building can mitigate these variations. This is done, specifically for temperature, which is the most critical aspect. Thanks to a continuous monitoring system for indoor and outdoor thermo-hygrometric parameters, a Multiple Linear Regression model is developed in order to predict and analyse the indoor temperature trend. This model allows to estimate a future forecast of this parameter and to predict in advance critical conditions for correct conservation.

Improving the Spring Air Temperature Forecast Skills of BCC_CSM1.1 (m) by Spatial Disaggregation and Bias Correction: Importance of Trend Correction

In this study, an improved method named spatial disaggregation and detrended bias correction (SDDBC) based on spatial disaggregation and bias correction (SDBC) combined with trend correction was proposed. Using data from meteorological stations over China from 1991 to 2020 and the seasonal hindcast data from the Beijing Climate Center Climate System Model (BCC_CSM1.1 (m)), the performances of the model, SDBC, and SDDBC in spring temperature forecasts were evaluated. The results showed that the observed spring temperature exhibits a significant increasing trend in most of China, but the warming trend simulated by the model was obviously smaller. SDBC performed poorly in temperature trend correction. With SDDBC, the model’s deviation in temperature trend was corrected, and consequently, the temporal correlation between the model’s simulation and the observation as well as the forecasting skill on the phase of temperature were improved, thus improving the MSSS and the ACC. From the perspective of probabilistic prediction, the relative operating characteristic skill score (ROCSS) and the Brier skill score (BSS) of the SDDBC for three categorical forecasts were higher than those of the model and SDBC. The SDDBC’s BSS increased as the effect of the increasing resolution component was greater than that of the decreasing reliability component. Therefore, it is necessary to correct the predicted temperature trend in post-processing for the output of numerical prediction models.

Analysis of Decadal Rainfall and Temperature Trend in Warri, Nigeria

This study investigates rainfall and temperature trend in Warri, Delta State, Nigeria using data derived from Nigerian Meteorological Agency between 2005 and 2015. Data was analyzed to reveal trend in temperature and rainfall values in the years under study and to determine whether there were significant variations. Analysis of rainfall data shows that 2007 had the lowest total rainfall over the 11 year period with a total annual rainfall of 2030.58 mm while 2015 was the year with the highest annual rainfall record of 3183.6 mm. The mean monthly Rainfall indicates that January has the lowest record of rainfall with a total of 36.9 mm while July is the month with highest value of 423.2 mm. Results further indicates that June has the lowest mean monthly temperature over the 11 year period of 20 ºC while March has the highest record of 29.6 ºC. Dominant temperature ranges between 26.1 oC and 26.8 ºC closely followed by 27.7–28.4 ºC which are quite close to the mean monthly values in the area. Analysis of rainfall data confirms an increasing trend.

Spatial patterns of multi-centennial temperature trend in Antarctica over 0-1000 CE: insights from ice core records and modeling

<p>Recent Antarctic surface climate change has been characterized by greater warming trends in West Antarctica than in East Antarctica. Although the changes over recent decades are well studied, the short instrumental record limits our ability to determine if such asymmetric patterns are common for Antarctica and the processes at their origin. Here, we will focus on the years 0-1000 CE as some ice core records display very contrasted trends during this period. Furthermore, the climate models are unable to reproduce the warming displayed in some reconstructions from 1 to 500 CE over East Antarctica. In order to understand the origin of these apparent incompatibilities and investigate the effect of proxy selection on regional reconstructions over 0-1000 CE, we performed several offline data assimilation experiments based on different groups of d<sup>18</sup>O records and the isotope-enabled general circulation models (iCESM). When assimilating different d18O data sets, large differences appear in the pattern of temperature trend over 0-500 CE, but the patterns over 500-1000 CE are more consistent among the various experiments. This implies that the spatial pattern of temperature trend over 0-500 CE is still uncertain because of this high sensitivity on the choice of the proxies to constrain the model results, while the pattern over 500-1000 is more robust, with the greater cooling over West Antarctica than East Antarctica. This pattern over 500-1000 CE relates to the intensifying of the low pressure centered in the Amundsen Sea, which induces enhanced southerly flow through most of WAIS.</p>