Reliability of Existing Climate Indices in Assessing the Freeze-Thaw Damage Risk of Internally Insulated Masonry Walls

This paper evaluates the reliability of the currently used climate-based indices in selecting a moisture reference year (MRY) for the freeze-thaw (FT) damage risk assessment of internally insulated solid brick walls. The evaluation methodology compares the ranking of the years determined by the climate-based indices and response-based indices from simulations, regarded as actual performance. The hygrothermal response of an old brick masonry wall assembly, before and after retrofit, was investigated in two Canadian cities under historical and projected future climates. Results indicated that climate-based indices failed to represent the actual performance. However, among the response-based indices, the freeze-thaw damage risk index (FTDR) showed a better correlation with the climate-based indices. Additionally, results indicated a better correlation between the climatic index (CI), the moisture index (MI), and FTDR in Ottawa; however, in Vancouver, a better fit was found between MI and FTDR. Moreover, the risk of freeze-thaw increased considerably after interior insulation was added under both historical and projected future climates. The risk of FT damage would increase for Ottawa but decrease for Vancouver under a warming climate projected in the future, based on the climate scenario used in this study. Further research is needed to develop a more reliable method for the ranking and the selection of MRYs on the basis of climate-based indices that is suitable for freeze-thaw damage risk assessment.

Rainfall Variability and its Impact on Crop Production in Niger State, Nigeria

The net potential effect of severe changes in rainfall pattern disrupts crop production leading to food insecurity, loss of jobs, and poverty. Crop production in Niger State is predominantly rain-fed, thus, exposing this major livelihood activity to the variability of rainfall. The study examined the impact of rainfall variability and its consequences on crop production. This is to integrate climate change adaptation options into agricultural activities. Strategies for climate change adaptation options in the study area have often been made without experimental foundations placed on the level of rainfall variability and its implications on crop production. To achieve this, a climatic index (CI) analysis of rainfall was employed to ascertain the level of rainfall extremes occurrences resulting from rainfall variability using standard deviation as a tool for rationalization. The study also used crop yield to test the relationship between the yield and rainfall characteristics for thirty years (1990-2019). Rainfall data and crop yield (soybean, maize, and sorghum) were collected. The data were analysed using statistical and climatic index analyses. The results show that there were various degrees of rainfall extremes that occurred (from mild to severe dry spell and mild to severe wet spell). Moreover, the regression analysis shows that F-values > p-values. Consequently, the occurrences of severe wet spells and mild to severe dry spells impacted negatively on crop production, which undermines food security. Based on the findings, recommendations were made to mainstream the adaptation options.

Nonlinear reconstruction of bioclimatic outdoor-environment dynamics for the Lower Silesia region (SW Poland)

Measured meteorological time series are frequently used to obtain information about climate dynamics. We use time series analysis and nonlinear system identification methods in order to assess outdoor-environment bioclimatic conditions starting from the analysis of long historical meteorological data records. We investigate and model the stochastic and deterministic properties of 117 years (1891–2007) of monthly measurements of air temperature, precipitation and sunshine duration by separating their slow and fast components of the dynamics. In particular, we reconstruct the trend behaviour at long terms by modelling its dynamics via a phase space dynamical systems approach. The long-term reconstruction method reveals that an underlying dynamical system would drive the trend behaviour of the meteorological variables and in turn of the calculated Universal Thermal Climatic Index (UTCI), as representative of bioclimatic conditions. At longer terms, the system would slowly be attracted to a limit cycle characterized by 50–60 years cycle fluctuations that is reminiscent of the Atlantic Multidecadal Oscillation (AMO). Because of lack of information about long historical wind speed data we performed a sensitivity analysis of the UTCI to three constant wind speed scenarios (i.e. 0.5, 1 and 5 m/s). This methodology may be transferred to model bioclimatic conditions of nearby regions lacking of measured data but experiencing similar climatic conditions.

Investigation of long-term changes of coastal wave directionality patterns and their connections with NAO climatic index: UK case study

<p>The effects of climate change are at the spotlight of scientific research. In coastal science the effects of sea-level rise (SLR) on coastal areas, mainly as a result of melting of ice sheets and thermal volume expansion consist an intensive area of research. As well the changing ocean wave field due to greenhouse effect and interactions of atmospheric processes is under investigation. Researchers have placed focus on significant wave height changes and their associated impacts on the coastal environment, with evidence suggesting that the number, intensity and location of storms will change. It is suggested that equal attention should be placed on the mean wave direction changes and the effects that these changes may have on the coastlines and surrounding coastal infrastructure. Following that, this study investigated the changes in wave direction data since 1979 to 2019 covering 40 years’ time period at 11 offshore UK coastal locations. The selected locations lie close to WaveNet, Cefas’ strategic wave monitoring network points for the UK. Stakeholders use the data to provide advice and guidance to all involved parties including responders and communities about coastal flood risk. On a longer timescale the data provide evidence to coastal engineers and scientists of the wave climate change patterns and the implications this may have on coastal structures and flood defences design. Based on this initiative, this study investigated UK offshore wave climate changes by performing a longer timescale analysis of changes of wave direction patterns. The wave direction data were taken from ECMWF ERA5 6-hour hind cast data catalogue which covers 40 years’ time period from 1797-2019 (Copernicus Climate Change Service (C3S), 2017). MATLAB software coding was primarily utilized for data processing and analyses. Following that, inferential statistics were applied to map inter-decadal statistical changes in wave direction patterns, suggesting that wave directionality patterns have presented changes at 11 offshore locations tested.  The connections of wave directions with North Atlantic Oscillation (NAO) Climatic Index are currently investigated through use of machine learning approaches. The results of this study can be confidently used in wave transformation computational models coupled with hydro-morphodynamic models to downscale offshore wave direction changes to UK coastal areas. This can help identify susceptible coasts to offshore wave climate change. Susceptibility is regarded in form of coastal erosion and accretion rates changes as a result of altered offshore wave conditions, which might affect coastal flood risk with potential impacts on critical infrastructure.  </p>

Assessment climate resource of Con Dao island (Vietnam) by using the tourism climate index

This article assesses climatic conditions for tourism by using Tourism Climate Index - TCI, published by Mieczkowsk (1985). This is an experimental synthetic climatic index that evaluates simultaneously the influence of 7 climatic elements as maximum average temperature (oC), minimum average humidity (%), average temperature (oC), average humidity (%), the number of sunny hours, windy speed of Con Dao island. The results of TCI within 12 months in Con Dao island compare to “Classification of advantageous levels of climate for tourism” of TCI (Mieczkowsk, 1985) which shows the advantages of Con Dao for relaxation tourism all year round. The period from December to April is the most favourable time for tourism activities in Con Dao because the TCI index reaches from Good to Very good, while the suitable time is from May to November, due to rainfall and high speed of wind during the rainy season.

Mineralogy and geochemistry of the Ossa lake Complex sediments, Southern Cameroon: implications for paleoweathering and provenance

This study investigates the provenance, paleoweathering, and paleoclimate of the Ossa lake sediments, based on the mineralogy and geochemistry data. Ossa lake sediments are characterized by silt and clay with high content of total organic carbon (TOC). Clay minerals are identified as kaolinite and illite types. Other dominant minerals identified are quartz, zircon, rutile, goethite, gibbsite, feldspar, and accessory vivianite. The major, trace, and rare earth element concentrations indicate that the sediments were derived from felsic rocks, such as gneisses and granitoids. The tectonic discrimination diagrams revealed an active margin setting. Weathering indices such as the chemical index of alteration (CIA), the plagioclase index of alteration (PIA), and chemical index of weathering (CIW) suggest intense chemical weathering in the source area. K2O/Na2O ratio and index of compositional variation (ICV) are consistent with high maturity of the sediments. The mineral assemblages and trace elemental ratios and climatic index “C” of the Ossa Lake sediments suggest a warm to semi-humid climate and deposition in an oxic shallow environment.

Dengue and SARS-CoV-2 Co-Circulation Early Warning according to Climate Variations in Cuba

Dengue and Severe Acute Respiratory Syndromes Coronavirus 2 (SARS-CoV-2) co-circulation is a reality resulting to be more dangerous in regions that are endemic for arboviruses. Circulation of both viruses continue spreading, mainly in tropical settings causing a high impact on the health systems of the countries. Therefore, forecasting the circulation of SARS-CoV-2 virus and dengue from the climatic variability a temporal and spatial scale allows to perfect the warning system and provides a tool for decision makers in the health system to take the necessary control measures. Methods: Ecological study with retrospective-prospective analysis of the series of the SARS- CoV-2 viruses, dengue, as well as, Aedes focus with their index and the climatic anomalies described by the complex climatic Index of Bulto (BI1, r, t). Interpolation method for the spatial structure with continuous information of 1200 nodes (Raster format) was generated. Kriging method combined with the method of the inverse distance (IDM) was implemented with a resolution of 10 km2 . The Multivariate Moran Index was used to determine the spatial correlation. For the prediction, the Simultaneous Autoregressive Models and the Spatial Autoregressive Conditional Models were used. Temporal modeling was carried out by using the Heteroscedastic Conditional Autoregressive and Autoregressive Models, both with exogenous variables. To obtain the co-circulation risk forecast maps, a stratification of the circulation of both viruses is carried out and map algebra is applied. Results: The moments of greatest risk Dengue and SARS-CoV-2 co-circulation are the months corresponding to the second quarter of the rainy period August-October with very humid conditions, very high temperatures, high volume of precipitation, high cloudiness, being potential predictors. All these results led to the creation of the dengue alert system and co-circulation with SARS-CoV-2 based on the observation and forecast of climatic factors. The areas with major viral co-circulation were the Central-Eastern region. Conclusions: It is evident that the climate is an important determinant for the health sector, and in particular to understand the Dengue and SARS-CoV-2 behavior and co-circulation, which strengthens the active health surveillance system.

A Recent Study of the Relationship between the Precipitation Rate over Saudi Arabia in the Fall and Climatic Indices

This paper presents a recent study of the relationship between precipitation rate (PR) over Saudi Arabia (SA) within the months of the fall season and climatic indices. The fall monthly PR data spanning the study period between 1948 and 2018 is considered. In addition, the monthly climatic index records (arctic oscillation (AO), global surface air temperature (GSAT), multivariate ENSO index (MEI), North Atlantic Oscillation (NAO) index, Nino 3.4 index, and Southern Oscillation Index (SOI)) for the fall months were also considered. The statistical trend, anomaly, and correlation analyses are applied in this study. The results reveal that the sweeping changes in PR show generally positive trends throughout the fall seasons of the past decades. Moreover, the climatic indices have an effect on the PR over SA within the fall months and season. During the study period, the most substantial relationship recorded, with an inverse correlation of −0.7, is between the PR over SA and the climatic index of GSAT for September and October. Moreover, there is a clear correlation of +0.5 between the PR over SA and the ENSO and Nino 3.4 index for October and November.