Temperature Trends Research Articles

Trends in temperature and precipitation at high and low elevations in the main mountain ranges of the Iberian Peninsula (1894–2020): The Sierra Nevada and the Pyrenees

AbstractThis study describes temperature and precipitation trends in the two National Parks located in the two highest mountain ranges on the Iberian Peninsula: the Sierra Nevada (Sierra Nevada National Park, SN) and the Pyrenees (Aigüestortes i Sant Maurici National Park, ASM). Special focus is placed on analysing disparities between the lowlands and the highlands, as well as the agreement between observational data and grid data (IBERIA01 and E‐OBS). For this purpose, a quality‐controlled and homogeneity‐adjusted database of the daily maximum temperature, minimum temperature and precipitation (SMADS database) has been generated. Regional trends in mean temperature indicate that warming in ASM (0.17°C·decade−1) was greater than in the Sierra Nevada (SN) (0.13°C·decade−1) in the longest joint period, 1930–2020. For annual precipitation, the trends over the past nine decades were negative, although not significantly. Only the summer in SN showed a significant negative trend, which has intensified in recent decades to −13.4%·decade−1 for 1975–2020. A parallel evolution was observed in the annual mean temperature of the highlands (>1500 m) and lowlands (<1500 m) of ASM, with a common trend of 0.17°C·decade−1, while in SN negative elevation‐dependent warming was detected. Differences between lowlands and highlands were also noted in precipitation trends in both mountain ranges: a positive trend in precipitation was found in the lowlands while in the highlands practically null trends (ASM) or decreasing precipitation trends (SN) were detected. The comparison of the Spanish Mountain Adjusted Daily Series (SMADS) results with the IBERIA01 and E‐OBS grid series yielded differences no greater than ±0.2°C·decade−1. No notable differences were detected between the regional trends calculated with observational series or with grid series. These results worsened when the differences in the trends detected in the individual observed temperature series were compared against the corresponding grid series.

Global total precipitable water variations and trends over the period 1958–2021

Abstract. Global responses of the hydrological cycle to climate change have been widely studied, but uncertainties still remain regarding water vapor responses to lower-tropospheric temperature. Here, we investigate the trends in global total precipitable water (TPW) and surface temperature from 1958 to 2021 using ERA5 and JRA-55 reanalysis datasets. We further validate these trends using radiosonde from 1979 to 2019 and Atmospheric Infrared Sounder (AIRS) and Special Sensor Microwave Imager/Sounder (SSMIS) observations from 2003 to 2021. Our results indicate a global increase in total precipitable water (TPW) of ∼ 2 % per decade from 1993–2021. These variations in TPW reflect the interactions of global warming feedback mechanisms across different spatial scales. Our results also revealed a significant near-surface temperature (T2 m) warming trend of ∼ 0.15 K decade−1 over the period 1958–2021. The consistent warming at a rate of ∼ 0.21 K decade−1 after 1993 corresponds to a strong water vapor response to temperature at a rate of 9.5 % K−1 globally, with land areas warming approximately twice as fast as the oceans. The relationship between TPW and T2 m showed a variation of around 6 % K−1–8 % K−1 in the 15–55° N latitude band, aligning with theoretical estimates from the Clausius–Clapeyron equation.

Long-term trend and variability in surface temperatures over Emilia-Romagna from 1962 to 2022

Scientific interest is increasingly drawn towards regional meteorological extremes, given their impacts on populations, infrastructure, and ecosystems. These extremes are shaped by complex interactions between internal climate variability and long-term trends. The aim of the present work is to evaluate changes in high-frequency variability and the influence of long-term trends on the frequency of occurrences of extremes, with a focus on surface temperatures over the period from 1962 to 2022 in Emilia-Romagna, a region of Northern Italy. Daily data of 2 m air temperatures averaged over the region are retrieved from ERACLITO, a high-resolution climate analysis. The distributions of daily temperature anomalies show a general broadening in 1992–2022 with respect to 1962–1991. This is true for maximum, minimum, and mean daily surface temperatures, especially during the summer and spring seasons. A significant warming trend of 0.37 °C/decade is detected in annual mean surface temperatures over the period considered. The study is completed with a comparison between the observed frequency of record-breaking annual temperature events, a hypothetical stationary climate distribution and a theoretical derivation that accounts for changes in trends and variability. During the last decade, the theoretical count of extreme events is 1.26, which yields a likelihood of 86% that this is owed to the trend rather than interannual variability. Idealized experiments demonstrate that the expected occurrences of record-breaking events in future decades depend on the warming rate rather than the warming level. Finally, an analysis performed at seasonal level shows that the majority (minority) of record events are occurring in the summer (spring) seasons.

Drivers of Changes to the ENSO–Europe Teleconnection Under Future Warming

AbstractThe El Niño–Southern Oscillation (ENSO) teleconnection to Europe is projected to strengthen under global warming in most climate model simulations. However, given the current difference between recent observations and historical model simulations of tropical Pacific sea surface temperature trends, with models simulating an El Niño‐like warming in recent decades which is in disagreement with observations, it is important to understand the relative contributions of changes to the teleconnection forcing and background state to the overall teleconnection change. Using idealized climate model experiments, we show that both the eastward shift of El Niño precipitation and background state changes make contributions to the overall teleconnection change. These results suggest that the ENSO–Europe teleconnection can be expected to strengthen under global warming, even if ENSO precipitation anomalies do not shift eastwards as currently projected. However, the magnitude of the strengthening may depend on how much of an eastward shift does occur.

Dual-comb spectroscopy of ammonia formation in non-thermal plasmas

Plasma-activated chemical transformations promise the efficient synthesis of salient chemical products. However, the reaction pathways that lead to desirable products are often unknown, and key quantum-state-resolved information regarding the involved molecular species is lacking. Here we use quantum cascade laser dual-comb spectroscopy (QCL-DCS) to probe plasma-activated NH3 generation with rotational and vibrational state resolution, quantifying state-specific number densities via broadband spectral analysis. The measurements reveal unique translational, rotational and vibrational temperatures for NH3 products, indicative of a highly reactive, non-thermal environment. Ultimately, we postulate on the energy transfer mechanisms that explain trends in temperatures and number densities observed for NH3 generated in low-pressure nitrogen-hydrogen (N2–H2) plasmas.

The relationship between elevation-dependent warming and long-term trend of surface air temperature lapse rate

The intensity and direction of elevation-dependent warming (EDW) could vary in different parts of the mountain, while less attention is paid to the local EDW effect. The Tibetan Plateau (TP) and the T'ai-hang & Lvliang Mountains in Shanxi Province of China (TLMsx) were taken as cases to examine the relationship between EDW and the long-term trend of surface air temperature (SAT) lapse rate (SATLR). For the observed data, the intensity of regional EDW (IEDW) was estimated with linear regression model, while the SATLR was estimated with geographically weighted regression (GWR) model. The long-term trend of SATLR was estimated applying the modified Theil-Sen method, and the regional average SATLR trend (kSATLR¯) was calculated and analyzed. Both observed data and simulation experiment revealed that there was not significant difference between IEDW and −kSATLR¯, with a little difference caused by the noise in the SAT trends. As the SATLR trend measured the difference in the surface air warming rate within 1-km vertical distance, i.e. the intensity of EDW in a small spatial scale, in the context of climate warming, it could be used to estimate the intensity of local EDW. The SATLR trend thus provided a new perspective to study the EDW effect in the future, and facilitated the quantitative analysis on the mechanisms of EDW.

Projections of temperature and precipitation trends using CMhyd under CMIP6 scenarios: A case study of Iraq's Middle and West

Climate change is becoming a leading issue in the 21st century due to its devastating environmental and socioeconomic impacts. It is believed to have significant impacts on the water resources and groundwater in the Middle East region, especially in Iraq. In this study, three different global climate models, under the 6th IPCC report, were downscaled under two SSPs scenarios in the middle and west of Iraq. The downscaled models were fixed for bias using CMhyd (climate model data for hydrologic modeling) over the study area. This was achieved using data from four locally chosen weather stations from 1983 to 2022. Three CMIP6 global models were considered and compared. These were the Australian Community Climate and Earth-System Simulator version 1 (ACCESS-CM2), the Beijing Climate Center Climate System Model version 2 (BCC-CSM2-MR), and the sixth version of the Model for Interdisciplinary Research on Climate (MIROC6).The findings of this study show that the temperature and precipitation changes in the three models under two scenarios in the future period (2023–2050) show an increasing trend compared to the observation period (1983–2014). The results of the generated predictions show that there will be an increase in annual maximum temperatures by this century's end, by 1.26–2.08 °C under scenario SSP2–4.5 and 1.57–2.34 °C under scenario SSP5–8.5 across all study stations. The study found that the annual increase in precipitation over the observed period varies between scenarios (SSP2–4.5 and SSP5–8.5), ranging from +3.56 to +3.87% for SSP2–4.5 and + 7.22% to +12.61% for SSP5–8.5. The results should help improve our understanding of the effects of climate change on the study region and encourage planners and stakeholders to identify optimal strategies for mitigating them.

Elevation dependent climate assessment and its influence on snow cover variability in Hindu Kush Himalayan region using Google Earth Engine for the period of 2003–2021

The Hindu Kush Himalayan (HKH) regions are taken for this study, which is predominantly characterized by amplified climatic uncertainty and rapid snow melting. Because at the present there is a lack of studies estimating the elevation dependent and climate influenced snow cover variability in the HKH region. This present study examines elevation-dependent (2003–2021) distribution and trends in precipitation, temperature, and snow cover area (SCA) by employing numerous non-parametric statistical applications using the Google Earth Engine (GEE). The Modified Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow cover data is employed to estimate SCA along with the Climate Hazards Group Infrared Precipitation with Station Data version 2.0 (CHIRPS-V2.0) for precipitation and MODIS land surface temperature (LST). The study reveals statistically significant decreasing annual, seasonal, and monthly trends of SCA in most of the elevation zones typically during winter season (−0.256%/year), whereas temperature and precipitation exhibit strong spatial variability. Inclusive investigation portrays maximum mean annual and seasonal increased precipitation at the low-elevated regions, whereas seasonal disparities in temperature ostensible marginal decreased at high-elevation, albeit increased at lowland. Moreover, topographic importance on SCA distribution showcases maximum snow (43.4%) at north-facing less surface inclination with flat topography (14.6%). The comprehensive elevation wise analysis improves our understanding of the overall hydrological challenge and assist in the development of more reliable flood forecasting and water resource management.

Asymmetric warming has different impacts on vegetation growth across various vegetation types on the Tibetan Plateau

ABSTRACT Global warming could affect vegetation growth, while land surface temperature has exhibited an asymmetric warming pattern over the past 50 years. The Tibetan Plateau, known as “the roof of the world,” experiences the surface warming almost twice as high as the global average. However, previous research has largely overlooked the impacts of this asymmetrical warming on vegetation growth and the temporal changes in these impacts. In this study, we assess the effects of asymmetric warming on vegetation growth at regional and different vegetation types by using partial correlation analysis, and reveal the temporal changes of impacts strength using time moving window. The results showed that there had been a significant greening trend (1.01 × 10−3 yr−1, p < 0.01) in the Normalized Difference Vegetation Index (NDVI) during the growing season, as well as significant warming trends in both maximum temperatures (Tmax, 0.0354°C yr−1, p < 0.01) and minimum temperatures (Tmin, 0.0333°C yr−1, p < 0.01) during 2000–2021. Under the background of asymmetric warming, the grassland showed stronger impacts of Tmin than Tmax on NDVI, while the opposite effects were observed for forests. Over time, the response of NDVI to Tmax and Tmin has intensified. This study highlights importance of asymmetric warming in the projection of climate change on vegetation in similarly vulnerable ecosystems worldwide.

Spatio-Temporal Trends in Precipitation, Temperature, and Extremes: A Study of Malawi and Zambia (1981–2021)

Analyzing long-term climate changes is a prerequisite for identifying hotspot areas and developing site-specific adaptation measures. The current study focuses on assessing changes in precipitation, maximum and minimum temperatures, and potential evapotranspiration in Zambia and Malawi from 1981 to 2021. High-resolution precipitation and temperature datasets are used, namely, Climate Hazards Group InfraRed Precipitation with Station data (0.05°) and Multi-Source Weather (0.1°). The Mann–Kendall trend test and Sen’s Slope methods are employed to assess the changes. The trend analysis shows a non-significant increase in annual precipitation in many parts of Zambia and Central Malawi. In Zambia and Malawi, the average annual and seasonal maximum and minimum temperatures show a statistically significant increasing trend (up to 0.6 °C/decade). The change in precipitation during the major rainy seasons (December–April) shows a non-significant increasing trend (up to 3 mm/year) in a large part of Zambia and Central Malawi. However, Malawi and Northern Zambia show a non-significant decreasing trend (up to −5 mm/year). The change in December–April precipitation significantly correlates with El Niño–Southern Oscillation (Indian Ocean Dipole) in Southern (Northern) Zambia and Malawi. To minimize the impact of the observed changes, it is imperative to develop adaptation measures to foster sustainability in the region.

Spatio−Temporal Changes and Key Driving Factors of Urban Green Space Configuration on Land Surface Temperature

Changes in land cover by rapid urbanization have diminished the cooling effect of urban green spaces (UGS), exacerbating the upward trend of land surface temperature (LST). A thorough and precise understanding of the spatio-temporal characteristics of UGS and LST is essential for mitigating localized high temperatures in cities. This study identified the spatio-temporal changes in UGS configuration and LST in Shanghai from 2003 to 2022. The correlation between UGS configuration and LST was explored using spatial autocorrelation analysis and causal inference. The results show that (1) the high-temperature space had grown from 721 km2 in 2003 to 3059 km2 in 2022; (2) in suburbs, the largest area of UGS tended to decrease, while the number of patches tended to increase, indicating a distinct feature of suburbanization; (3) changes in the largest area of UGS had more significant spatial correlation, indicating that urban sprawl primarily impacts large UGSs; and (4) compared to the number and shape of UGS, changes in the largest area are the key factor influencing regional LST. These findings enrich the knowledge of the spatio−temporal relationship between the UGS configuration and its cooling effect in urbanization, offering valuable insights for building cooler cities.

PSI-7 Hourly flushing rates and temperature trends for electronically controlled grouped floor cooling pads trends during the summer heat stress in a boar stud

Abstract The objective of the study was to evaluate the flushing management trends of the electronically controlled grouped floor cooling pads (ECP) during the summer heat stress in a boar stud at Scottsville, Kentucky. Four groups of 5 ECPs connected to each other were placed in 15 boar crates (2.06 x 0.66 m) in a 350 head evaporative cooled, tunnel ventilated barn. One set of ECP (Zone 1) had temperature sensors placed on the 5th pad which triggers flushing of 4.25 L cold water (over 80 sec interval) when sensors reached 27°C. The other two sets of ECP (Zones 2 and 5) had temperature sensors on the first pad and flushing the same cold-water volume when sensors reached 24°C (based on the first pad averaging 3°C lower temperature than the last pad) or every 4 min, whichever occurred first. Cold water for Zone 1 and 2 came from cooling tank 1 (Mean = 17.35°C) while Zone 5 cold water came from cooling tank 2 (Mean = 15.7°C). The water in both tanks was cooled using a 2 HP Hydro Frost Chiller. Daily ECP temperatures (PT), ECP flushing rate (FR), barn temperature (BT) barn relative humidity (RH) barn dewpoint (DP) and cooling tank temperature (TT) were collected every 10 min for the ECP variables and 30 mins for the environmental variables. Boars experienced varying natural summer heat stress (temperature and corresponding relative humidity and dewpoint: Mean = 25.3°C, 87.2%, 23.2°C; high: 29.0°C, 84.5%, 26.1°C), July 29, 2023. A mixed model was used for statistical analysis in SAS including fixed effects of zone and hour. FR and PT readings were affected by the zone, hour of day and all two- and three-way interactions (P &amp;lt; 0.001). All of the zones flushed more frequently late morning to afternoon (Mean: 64.6%) from 1100 to 1600 h and gradually the FR decreased in the evening (1900 h onwards). Zone 1 flushed more frequently (47.7%) than the 2 other zones (Zone 2 = 39.9%, Zone 5 = 33%). Zone 1 ECP temperature averaged 26.7°C (hourly mean range 26.1°C to 27.3°C). Zone 2 ECP temperatures averaged 22.1°C (hourly mean range 19.7°C to 24.1°C). Zone 5 ECP temperature patterns averaged 20.7°C (hourly mean range 19.1°C to 22.4). Zone 1 flushed less frequently (30.3%) at between 2100 to 0400 h. The following day and PT stayed cooler (Mean = 26.7°C) compared with the PT during the middle of the day (27.1°C).The set temperature (27°C; 24°C) or set time every 4 min kept the temperature of the ECP at desirable temperature, below 27°C for the last boar pad or below 24°C for the first of 5 pads (with approximate 3°C difference between the first and last of the of the 5 pads).

Evapotranspiration Analysis in Central Italy: A Combined Trend and Clustering Approach

Climate change is increasingly influencing the water cycle, hindering the effective management of water resources in various sectors. Lazio, central Italy, exhibits a wide range of climatic conditions, stretching from the Tyrrhenian coast to the Apennines. This study assessed a crucial aspect of climate change, focusing specifically on reference evapotranspiration (ETo) and its associated hydrological variables. The seasonal Mann–Kendall (MK) test was used to assess trends in gridded data. The K-means algorithm was then applied to divide Lazio into four homogeneous regions (clusters), each characterized by distinct trends in hydrological variables. The analysis revealed statistically significant increasing trends (p ≤ 0.01) in temperature, solar radiation, and ETo, with more marked effects observed in the coastal and hilly clusters. In contrast, statistically significant decreasing trends (p ≤ 0.01) were observed for relative humidity, while no statistically significant trends (p &gt; 0.01) were observed for precipitation. This study’s methodology, combining trend analysis and clustering, provides a comprehensive view of ETo dynamics in Lazio, aiding in pattern recognition and identifying regions with similar trends.

Radiative bioconvective flow with non-uniform heat source and Soret and Dufour impacts

Background and objectiveThe stretched flow with heat transfer has pivotal role in geothermal energy system, oil extraction, continuous casting, metal spinning and electronic cooling. Owing to this fact, the current analysis focuses on non-linear thermal radiation effect in bio-convective stagnation point flow by a stretchable wedge. Darcy relation is used to discuss the porous space. Convective conditions are deliberated. Non-uniform heat source is addressed. Soret and Dufour outcomes are analyzed. Dissipation and magnetohydrodynamics are discussed. Presence of gyrotactic microorganisms along with chemical reaction is considered. MethodologyRelated non-linear partial differential equations (PDEs) are reduced into dimensionless ordinary differential equations (ODEs) through adequate transformations. Optimal homotopy analysis method (OHAM) is adopted for the computations of related nonlinear differential systems. ResultsFlow, microorganism field, concentration and temperature distribution are graphically explored. Numerical analysis for coefficient of skin friction, microorganism density number and Sherwood and Nusselt numbers against emerging parameters are discussed. It is noted that velocity and skin friction coefficient have similar scenario for modified Hartman number. Thermal transport rate and temperature have reverse trends for non-uniform heat source variable. An augmentation in thermal distribution is seen through thermal Biot number. Larger Dufour number has increasing trend for temperature. An increasing trend for solutal Biot number for concentration is noticed. Larger Soret number leads to concentration enhancement. Microorganism field and motile density number against Peclet number have opposite response. There is reduction for bio-convective Lewis number in motile density number.

Response of radial growth of Pinus wallichiana to climate change in Mount Qomolangma, Tibet, China

Global warming would significantly impact tree growth in the Tibetan Plateau. However, the specific effects of climate change on the radial growth of Pinus wallichiana in Mount Qomolangma are still uncertain. To investigate the responses of radial growth of P. wallichiana to climate change, we analyzed tree-ring samples in Mount Qomolangma. We removed the age-related growth trends and established three chronologies by using the modified negative exponential curve, basal area index, and regional curve standardization, and conducted Pearson correlation and moving correlation analyses to examine the association between radial growth of P. wallichiana and climatic factors. The results showed that this region had experienced a significant upward trend in temperature and that the Palmer drought severity index (PDSI) indicated a decreasing trend since 1980s, while the relative humi-dity changed from a significant upward to a downward trend around 2004, implying the climate shifted toward warmer and drier. Results of Pearson correlation analysis indicated a significant and positive relationship between the radial growth of P. wallichiana and the minimum temperature of April-June and July-September, and precipitation of January-April in the current year. The radial growth of P. wallichiana was significantly and negatively associated with the relative humidity of June, July, and August in the current year. As temperature rose after 1983, the relationship between radial growth of P. wallichiana and the minimum temperature in July and September of the current year increased from a non-significant association to a significant and positive association, while the relationship between radial growth of P. wallichiana and relative humidity in August and precipitation in September of the current year changed from non-significant correlation to a significant and negative correlation. Results of the moving correlation analysis suggested that the radial growth of P. wallichiana showed a significant and stable correlation with the July-September minimum temperature of the current year. Under the background of climate warming, the rapid increases of temperature would accelerate the radial growth of P. wallichiana in Mount Qomolangma.

Evaluating Trends of Temperature Index in Gia Lai Province Based on IITA and IPTA Approaches under Climate Change

This study performs historical trend analysis for average, maximum, and minimum temperatures using the integration of the Improved visualization for trend analysis (IITA) and Innovative Polygon Trend Analysis (IPTA) of Şen to evaluate the tendency of extreme temperatures on different time scales (annual, monthly and seasonal) in Gia Lai province from 1980 to 2019 at three stations, including Pleiku, AyunPa, and An Khe. Results recorded over the past four decades, the temperature trend in Gia Lai has been gradually warming. The average temperature in each month of the year ranges from 19 to 28°C, December and January usually have the lowest temperature of the year with a variation lower than 20°C. On the contrary, the months of April, May, and June often have the highest temperatures of the year, with a variation greater than 26°C. The outcomes of this research have provided a general picture of temperature characteristics, useful information for the management and planning of land use, irrigation and water supply in Gia Lai province under unpredictable climate change.

Changes in precipitation and air temperature over Turkey using innovative trend pivot analysis method

Changes in precipitation and air temperature over Turkey using innovative trend pivot analysis method

Magnetic, dielectric and thermal study of CoNiFe2O4 nanoparticles

CoxNi1-xFe2O4 (x = 0.2–0.8) (CNFO) nanoparticles have been prepared using a low temperature hydrothermal technique. X-ray diffraction confirmed the cubic spinel structure of the nanoparticles, offering an increasing trend of lattice parameters from 8330 to 0.8345 nm as a function of Co-content. The microstructures were analysed using FESEM and TEM. The average grain size determined using FESEM images for x = 0.2–0.8 was found in the range from 110 to 183.7 nm. The TEM images show asymmetrical sphere-like particles, with the particle size changing from 69.4 to 82.1 nm as a function of ‘x’. The hysteresis curves were recorded for x = 0.2–0.8 to understand the ferrimagnetic behavior. The saturation magnetization (Ms) varies unsystematically between 35.3 and 43.3 emu/g with ‘x’, while a high magnetic moment of 1.819 μB/f.u. is found at a high Co-content. The paramagnetic term (χ x 10−5) goes on increasing from 125 to 148 emu/g.Oe with ‘x’. The zero-field cooled (ZFC) and field cooled (FC) curves provide the decreasing trend of variation blocking temperature (TB) from 270 to 260 for x = 0.2–0.6, whilst for x = 0.8, it is increased to 280 K. The high real part of the permittivity of ∼ 12.42 and low imaginary part of the permittivity of ∼0.638 are recorded at 8 MHz for x = 0.2, indicting energy storage applications. The power law fit was applied to log σac-log ω plots and the dc-electrical conductivity was evaluated. The TG-DTG and DSC curves revealed mass loss and transition temperatures for x = 0.2–0.8 as a function of temperature.

Monitoring Land Surface Temperature Trends in Indonesia

Monitoring Land Surface Temperature (LST) trends helps identify provinces vulnerable to temperature changes and aids in developing appropriate adaptation and mitigation strategies. This research article aims to monitor LST trends in Indonesia from 2000 to 2022 using MODIS Aqua Land Surface Temperature and Emissivity (MYD11A1) imageries. The study utilizes LST Day and LST Night datasets obtained from MYD11A1 datasets to achieve its research objective. Sens’ Slope is employed to identify and measure the magnitude and direction of temperature changes, while the Mann-Kendall trend test detects significant LST trends. GEE is used to process and analyze MODIS LST data. The findings show a significant increase in LST Night during the June-August (JJA) period in most provinces of Indonesia. LST Day data also stresses that some provinces in Indonesia are experiencing a warming trend. Elevation and population increases may contribute to the observed increasing LST trend. Notably, a short-term decrease in LST may occur within the long-term increasing LST trend.

Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases.

Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified. We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period. We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%). Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.