Strong Annual Cycle Research Articles

Climatological Aspects of Notable Tornado Events in Chile

Abstract Tornadoes in Chile seem to develop in what are called “high-shear, low-CAPE” (HSLC) environments. An analysis of convective parameters from the ERA5 reanalysis during 16 notable tornadoes in Chile showed that several increased markedly before the time of the reports. The significant tornado parameter (STP) was able to discriminate the timing and location of the tornadoes, even though it was not created with that goal. We established thresholds for the severe hazards in environments with reduced buoyancy (SHERBE) parameter (≥1) and the STP (≤−0.3) to further identify days favorable for tornado activity in Chile. The SHERBE and STP parameters were then used to conduct a climatological analysis from 1959 to 2021 of the seasonal, interannual, and latitudinal variations of the environments that might favor tornadoes. Both parameters were found to have a strong annual cycle. The largest magnitudes of STP were found to be generally confined to south-central Chile, in agreement with the (sparse) tornado record. The probability of a day with both SHERBE and STP values beyond their thresholds was greatest between May and August, which aligns with the months with the most tornado reports. The number of days with both SHERBE and STP beyond their respective thresholds was found to fluctuate interannually. This result warrants further study given the known interannual variability of synoptic and mesoscale weather in Chile. The results of this study extend our understanding of tornado environments in Chile and provide insight into their spatiotemporal variability.

Moisture Recycling in the Colombian Andes

AbstractThe Colombian Andes (CA) are located over the northwestern corner of tropical South America (NW‐TropSA), where land and atmosphere interchange moisture and energy in a complex way owing to the orographic influence on the recycling of moisture over land. We aim to understand where and when water vapor evaporated from land turns into rainfall through moisture recycling, using the Water Accounting Model‐2layers (WAM‐2), an offline model to track atmospheric moisture forced with data from ERA‐5 at its native 0.25° resolution during 1980–2020. We define the spatiotemporal distribution of sources (high evaporation recycle ratios, ϵC) and receptors (high precipitation recycle ratios, ρC) of continental moisture at diverse timescales, including monthly, seasonal, annual and interannual (ENSO). Referring to the regional runs of WAM‐2 over NW‐TropSA (4°S–12°N/80°W–66°W), at elevations above 1,000 m.a.s.l., the CA has a mean annual ρC of 11% (ranging 6%–16%) and a mean annual ϵC of 35% (ranging 27%–40%). Moisture recycling in the CA exhibits a strong annual cycle over the region. The seasonal dynamic of moisture recycling shows two clear‐cut sources of moisture: the eastern foothills of the Eastern and Central ranges of the CA. Both foothills are also regions of high rainfall, although moisture recycling mechanisms differ. Sources of continental moisture grow spatially during September‐October‐November and March‐April‐May. The seasonal availability of moisture recycled coincides with regions where orography interacts with low level jets sourcing humidity. At interannual timescales, sources and receptors of continental moisture in the CA are modulated by the extreme phases of ENSO.

Trend and Multi‐Frequency Analysis Through Empirical Mode Decomposition: An Application to a 20‐Year Record of Atmospheric Carbonyl Sulfide Measurements

AbstractThe Empirical Mode Decomposition (EMD) is a fully non‐parametric analysis of frequency modes and trends in a given series that is based on the data alone. We have devised an improved strategy based on a series of best practices to use EMD successfully in the analysis of the monthly time series of carbonyl sulfide (OCS) atmospheric mole fractions measured at NOAA network stations (2000–2020). Long‐term trends and intra‐ and inter‐annual variability has been assessed. After a phase of generally increasing mole fractions up to 2015, with a temporary decline around 2009, we found that the OCS atmospheric mole fraction subsequently decreased at all stations, reflecting a recent imbalance in its total sources and losses. Our analysis has revealed a characteristic time scale for variation of 8–10 years. The variance associated with this long‐term behavior ranges from 15% to 40% of the total strength of the signal, depending on location. Apart from this complex long‐term behavior, the OCS time series show a strong annual cycle, which primarily results from the well‐known OCS uptake by vegetation. In addition, we have also found one more frequency of minor variance intensity in the measured mole fraction time‐history, which corresponds to periods in the range of 2–3 years. This inter‐annual variability of OCS may be linked to the Quasi‐Biennial Oscillation.

Controlling factors of the climatological annual cycle of the surface mixed layer oxygen content: A global view

The annual cycle of global dissolved oxygen content (O2C) and mean oxygen concentration in the surface mixed layer are estimated using monthly climatological oxygen fields from the World Ocean Atlas 2018 (WOA18). The largest seasonal variability in the mixed layer O2C occurs in the extra-tropics between 30° and 70° latitude of each hemisphere. A global view of the role of entrainment, air-sea flux, and biological activity in controlling the oxygen content/concentration annual cycle in the mixed layer is determined using an oxygen mass balance model. Based on the relative percentage from the mass balance model, entrainment is only a significant driver (contributing to 20-40% of the total changes) from mid-fall to early spring when the mixed layer deepens and transfers oxygen to deeper waters. Both the air-sea oxygen flux and biological activity show strong annual cycles and play critical roles in the annual cycle of O2C in the mixed layer. Air-sea oxygen flux is ingassing from late fall to early spring and outgassing between late spring and early fall. It is a substantial factor throughout the year and controls 40-60% of the oxygen changes in most months. Biological activity is a net source (production) in the spring and summer and a net sink (consumption) in the late fall and winter for the mixed layer oxygen content. Biological activity plays a more important role during spring/summer (40-60%) than that during fall/winter (10-30%) in controlling the overall oxygen change in each month. The model estimates a mean value (±SD) of 3.06±1.61 mol C m-2 yr-1 and a total of 863.7±73.8 Tmol C yr-1 for the global annual net ocean community production (ANCP) between 60°S and 60°N latitude, which are in fairly good agreement with previous studies.

Sydney Harbour: Seiches, tides and mean circulation

Beginning with observations from 1901, sea level elevations and currents from Sydney Harbour are examined across a broad frequency range. The mean currents, annual components of sea level, tides and seiches, mainly in the South Arm, are the focus. Tidal and mean currents are ~0.01 m s-1. The general circulation is estuarine-like with a thin, near-surface outflow layer and a thicker, deeper inflow. The distribution of contaminants in bottom sediments suggests the circulation, though weak, plays a retentive role in the Arm, transporting sediments towards its head. Analysis of 11-years of sea level data indicates a strong annual cycle, more energetic during winter than from late spring to early fall. The increased energy occurred at all frequencies except for tides. Seiches, with periods of ~0.5 to 2 h, emerge as a strong contributor to sea level and currents. The distributions of elevation and flow amplitudes associated with seiches were derived. With maximum observed values of 0.74 m and 0.24 m s-1, seiche displacements and currents can exceed those associated with tides and the mean circulation. While earlier studies identified only the dominant fundamental seiche mode, recent sea level data sampled at 1-minute show that modes 2-4 occur. Keywords: Sydney Harbour, sea level, mean circulation, tides, seiches

Regional winds over the Iberian Peninsula (Cierzo, Levante and Poniente) from high‐resolution COSMO‐REA6 reanalysis

AbstractCierzo in the Ebro Valley and Levante and Poniente in the Strait of Gibraltar are three of the main winds over the Iberian Peninsula. However, their study is difficult due to the limited amount of observational data and available literature. In addition, current reanalysis products do not usually have sufficient resolution, generally greater than 10 km, to capture the orographic characteristics of these winds. In this study we explore the ability of high‐resolution COSMO‐REA6 reanalysis (6 km, 0.055°) to describe Cierzo, Levante and Poniente using HadISD observational data validation whenever it was possible. A numerical definition according to the characteristics of these winds is proposed through speed and directional range thresholds. Regional winds statistics, annual cycles, wind roses and covered areas are calculated. The results show a reasonable agreement between reanalysis and observations, with an annual average of 95 Cierzo days, and around 80 Levante and Poniente days for the whole period. These windy days typically extend around 21,000 km2 (or 600 reanalysis cells). Both extension and number of days present strong annual cycles and interannual variability. Several weather regimes associated to those regional wind days are obtained, in agreement with other comparable studies. Therefore, the study shows the capability of the high‐resolution COSMO‐REA6 reanalysis to capture and describe regional winds such as Cierzo, Levante and Poniente.

The annual cycle in scintillation time-scale of PMN J1726+0639

ABSTRACT We discovered rapid intra-day variability in radio source PMN J1726+0639 at GHz frequencies, during a survey to search for such variability with the Australia Telescope Compact Array. Follow-up observations were conducted over 2 yr and revealed a clear, repeating annual cycle in the rate, or characteristic time-scale, of variability, showing that the observed variations can be attributed to scintillations from interstellar plasma inhomogeneities. The strong annual cycle includes an apparent ‘standstill’ in April and another in September. We fit kinematic models to the data, allowing for finite anisotropy in the scintillation pattern. The cycle implies a very high degree of anisotropy, with an axial ratio of at least 13:1, and the fit is consistent with a purely one-dimensional scintillation pattern. The position angle of the anisotropy, and the transverse velocity component are tightly constrained. The parameters are inconsistent with expectations from a previously proposed model of scattering associated with plasma filaments radially oriented around hot stars. We note that evidence for a foreground interstellar cloud causing anomalous Ca ii absorption towards the nearby star Rasalhague (α Oph) has been previously reported, and we speculate that the interstellar scintillation of PMN J1726+0639 might be associated with this nearby cloud.

Large Circulation Patterns Strongly Modulate Long‐Term Variability of Arctic Black Carbon Levels and Areas of Origin

AbstractBlack Carbon (BC) aerosol is a major climate forcer in the Arctic. Here, we present 15 years (2001–2015) of surface observations of the aerosol absorption coefficient babs (corresponding to Equivalent BC), obtained at the Zeppelin Observatory, Ny Ålesund, Svalbard, coupled with backward transport modeling with Flexpart in order to calculate the Potential Source Contribution Function (PSCF) for BC. The observed long‐term variability superimposed on a strong annual cycle is studied as a function of large‐scale circulation patterns represented by monthly index values for the North Atlantic Oscillation (NAO) and the Scandinavian pattern (SCAN). We find a 35% increase of babs values at Zeppelin during the SCAN− phase in the winter half‐year compared to the SCAN+ phase but no significant difference in babs values between the NAO index phases. Both NAO and SCAN induce significant regional variability on the areas of origin of babs, mainly Siberia, Europe, and North America.

Seasonal fluctuations and geochemical modeling of acid mine drainage in the semi-arid Puna region: The Pan de Azúcar Pb–Ag–Zn mine, Argentina

Pan de Azúcar is an inactive Pb–Ag–Zn mine in the semi-arid Puna region of NW Argentina at 3600 m above sea-level. The mine is situated in Los Pozuelos basin, which is a UNESCO Biosphere Reserve. Substantial pyrite and few carbonate minerals are present in the tailings. The generated acid mine drainage (AMD) has low pH (1.92–4.06) and is mainly Fe–Zn–SO4 type water with high concentrations of metals that in order of relative abundance vary as: Al ≫ Cd > As(T) > Ni > V > Cu > Co > Sb > Cr > Pb > Sn > Ag. The strong annual cycle of dry and wet seasons in the Puna generates a significant influence on AMD geochemistry. In the dry season, there is no runoff and AMD drains mainly in the form of seepages with low pH (1.92–2.21), high concentrations of metals, and the formation of metal-rich soluble efflorescent salts is favored by strong evaporation. At the beginning of the wet season, the efflorescent salts rapidly dissolve and metals concentrations in AMD increase significantly, creating the most hazardous period for the surrounding fluvial environment. At the end of the wet season the pH increases (3.44–4.06) and the concentration of metals decreases, especially arsenic associated with ferric iron precipitates. As a consequence of the DC3 dam restoration, a large volume of AMD is retained forming an acid pond, in which processes of AMD mixing, secondary minerals precipitation, and sulfide oxidation were quantified by inverse modeling with mixing. Jarosite and schwertmannite precipitates in the surface of the pond and favors the attenuation of As and Pb. However, subaqueous oxidation of sulfide minerals, hydrolysis of silicates, and mixing with upstream AMD seepage increases the concentrations of SO42-, Fe(II), and the other metals in the seepage of the pond that migrates downstream. The results of this study indicate the necessity to improve the remediation methods of Pan de Azúcar mine. It is expected that other sulfide mines in the Puna region will have a similar variability of the AMD geochemistry, which should be considered for mine closure, remediation, and monitoring of water quality in mining.

A combined view on precipitation and temperature climatology and trends in the southern Andes of Peru

AbstractIn the southern Peruvian Andes, communities are highly dependent on climatic conditions due to the mainly rain‐fed agriculture and the importance of glaciers and snow melt as a freshwater resource. Longer‐term trends and year‐to‐year variability of precipitation or temperature severely affect living conditions. This study evaluates seasonal precipitation and temperature climatologies and trends in the period 1965/66–2017/18 for the southern Peruvian Andes using quality‐controlled and homogenized station data and new observational gridded data. In this region, precipitation exhibits a strong annual cycle with very dry winter months and most of the precipitation falling from spring to autumn. Spatially, a northeast–southwest gradient in austral spring is observed, related to an earlier start of the rainy season in the northeastern part of the study area. Seasonal variations of maximum temperature are weak with an annual maximum in austral spring, which is related to reduced cloud cover in austral spring compared to summer. On the contrary, minimum temperatures show larger seasonal variations, possibly enhanced through changes in longwave incoming radiation following the precipitation cycle. Precipitation trends since 1965 exhibit low spatial consistency except for austral summer, when in most of the study area increasing precipitation is observed, and in austral spring, when stations in the central‐western region of the study area register decreasing precipitation. All seasonal and annual trends in maximum temperature are larger than trends in minimum temperature. Maximum temperature exhibits strong trends in austral winter and spring, whereas minimum temperature trends are strongest in austral winter. We hypothesize, that these trends are related to precipitation changes, as decreasing (increasing) precipitation in spring (summer) may enhance maximum (minimum) temperature trends through changes in cloud cover. El Niño Southern Oscillation (ENSO), however, has modifying effects onto precipitation and temperature, and thereby leads to larger trends in maximum temperatures.

Observed variability of the West India Coastal Current on the continental slope from 2009–2018

We describe the variability of the West India Coastal Current (WICC) during 2009–2017 using data from acoustic Doppler current profilers (ADCPs) attached to moorings deployed on the outer shelf at a water-column depth of 100–200 m at three locations: off Kollam (9°N), Bhatkal (13.9°N), and Goa (15°N). Our study shows that the characteristics of the WICC on the outer shelf are similar to those observed on the slope except for the occasional decorrelation observed between them. Both shelf and slope WICC have a weak mean flow and a strong annual cycle. As seen on the slope, the depth of the undercurrent on the shelf changes with season because of the strong upward phase propagation associated with the annual cycle. Though the currents at all three shelf locations exhibit a strong seasonal cycle, there are prominent differences between the currents off the southwest coast of India (Kollam) and the central west coast of India (Bhatkal and Goa). The seasonal cycle off Kollam is often punctuated by strong intraseasonal bursts, which cause the shelf WICC off Kollam to be highly unpredictable; this unpredictability implies that on a given day of the year, one cannot expect a poleward (equatorward) current during the winter (summer) monsoon. On the central west coast, the poleward (equatorward) direction during the winter monsoon (summer monsoon) is prominent. Comparison with the available datasets shows that the WICC is occasionally coherent along and across the shelf, and the coherence is stronger for the seasonal cycle.

The Australian Northwest Cloudband: Climatology, Mechanisms, and Association with Precipitation

Abstract Australian northwest cloudbands (NWCBs) are continental-scale bands of continuous cloud that stretch from northwest to southeast Australia. In earlier studies, where the characteristics of NWCBs and their relationship with precipitation were identified from satellite imagery, there was considerable uncertainty in the results due to limited quality and availability of data. The present study identifies NWCBs from 31 years of satellite data using a pattern-matching algorithm. This new climatology is the longest record based entirely on observations. Our findings include a strong annual cycle in NWCB frequency, with a summer maximum and winter minimum, and a statistically significant increase in annual NWCB days over the period 1984–2014. Physical mechanisms responsible for NWCB occurrences are explored to determine whether there is a fundamental difference between summer and winter NWCBs as hypothesized in earlier studies. Composite analyses are used to reveal that a key difference between these is their genesis mechanisms. Whereas summer NWCBs are triggered by cyclonic disturbances, winter NWCBs tend to form when meridional sea surface temperature gradients trigger baroclinic instability. It was also found that while precipitation is enhanced over parts of Australia during a cloudband day, it is reduced in other regions. During a cloudband day, precipitation extremes are more likely over northwest, central, and southeast Australia, while the probability of extreme precipitation decreases in northeast and southwest Australia. Additionally, cold fronts and NWCBs can interact, leading to enhanced rainfall over Australia.

Spica and the annual cycle of PKS B1322–110 scintillations

PKS B1322-110 is a radio quasar that is located only 8.5' in angular separation from the bright B star Spica. It exhibits intra-day variability in its flux density at GHz frequencies attributed to scintillations from plasma inhomogeneities. We have tracked the rate of scintillation of this source for over a year with the Australia Telescope Compact Array, recording a strong annual cycle that includes a near-standstill in August and another in December. The cycle is consistent with scattering by highly anisotropic plasma microstructure, and we fit our data to that model in order to determine the kinematic parameters of the plasma. Because of the low ecliptic latitude of PKS B1322-110, the orientation of the plasma microstructure is poorly constrained. Nonetheless at each possible orientation our data single out a narrow range of the corresponding velocity component, leading to a one-dimensional constraint in a two-dimensional parameter space. The constrained region is consistent with a published model in which the scattering material is associated with Spica and consists of filaments that are radially oriented around the star. This result has a 1% probability of arising by chance.

Seasonality and the effects of weather on Campylobacter infections

BackgroundCampylobacteriosis is a major public health concern. The weather factors that influence spatial and seasonal distributions are not fully understood.MethodsTo investigate the impacts of temperature and rainfall on Campylobacter infections in England and Wales, cases of Campylobacter were linked to local temperature and rainfall at laboratory postcodes in the 30 days before the specimen date. Methods for investigation included a comparative conditional incidence, wavelet, clustering, and time series analyses.ResultsThe increase of Campylobacter infections in the late spring was significantly linked to temperature two weeks before, with an increase in conditional incidence of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship to temperature was not linear. Generalized structural time series model revealed that changes in temperature accounted for 33.3% of the expected cases of Campylobacteriosis, with an indication of the direction and relevant temperature range. Wavelet analysis showed a strong annual cycle with additional harmonics at four and six months. Cluster analysis showed three clusters of seasonality with geographic similarities representing metropolitan, rural, and other areas.ConclusionsThe association of Campylobacteriosis with temperature is likely to be indirect. High-resolution spatial temporal linkage of weather parameters and cases is important in improving weather associations with infectious diseases. The primary driver of Campylobacter incidence remains to be determined; other avenues, such as insect contamination of chicken flocks through poor biosecurity should be explored.

Seismicity of the Askja and Bárðarbunga volcanic systems of Iceland, 2009–2015

A large seismic network deployed in the Icelandic highlands recorded >100,000 earthquakes from 2009 to 2015. We develop a local magnitude scale, appropriate for use in central Iceland, which is similar to the scale used by the Iceland Meteorological Office. Using this large catalogue of earthquakes, we analyze the spatial and temporal changes in seismicity rates and b-values. In microearthquakes recorded from the usually ductile lower crust we find that b-values are high, reflecting the presence of high thermal gradients and low stresses driving seismicity associated with the movement of melt. In contrast, b-values in the upper crust are variable. Low b-values, indicative of a high stress environment, are observed during seismic swarms such as those around Mt. Herðubreið and around Bárðarbunga caldera. A persistently seismically active area around a geothermal area within Askja caldera has a b-value around 1 but has a strong annual cycle of seismicity. We attribute the annual cycle to varying load from the snow cover modulating the seismicity. Seismicity driven by the intrusion of a large dyke has a b-value well above 1, driven by the high pore fluid pressures and thermal gradients around the dyke.

Exploring the Impact of Climate Variability on Malaria Transmission Using a Dynamic Mosquito-Human Malaria Model.

Introduction:The reasons for malaria resurgence mostly in Africa are yet to be well understood. Although the causes are often linked to regional climate change, it is important to understand the impact of climate variability on the dynamics of the disease. However, this is almost impossible without adequate long-term malaria data over the study areas.Methods:In this study, we develop a climate-based mosquito-human malaria model to study malaria dynamics in the human population over KwaZulu-Natal, one of the epidemic provinces in South Africa, from 1970-2005. We compare the model output with available observed monthly malaria cases over the province from September 1999 to December 2003. We further use the model outputs to explore the relationship between the climate variables (rainfall and temperature) and malaria incidence over the province using principal component analysis, wavelet power spectrum and wavelet coherence analysis. The model produces a reasonable fit with the observed data and in particular, it captures all the spikes in malaria prevalence.Results:Our results highlight the importance of climate factors on malaria transmission and show the seasonality of malaria epidemics over the province. Results from the principal component analyses further suggest that, there are two principal factors associated with climates variables and the model outputs. One of the factors indicate high loadings on Susceptible, Exposed and Infected human, while the other is more correlated with Susceptible and Recovered humans. However, both factors reveal the inverse correlation between Susceptible-Infected and Susceptible-Recovered humans respectively. Through the spectrum analysis, we notice a strong annual cycle of malaria incidence over the province and ascertain a dominant of one year periodicity. Consequently, our findings indicate that an average of 0 to 120-day lag is generally noted over the study period, but the 120-day lag is more associated with temperature than rainfall. This is consistence with other results obtained from our analyses that malaria transmission is more tightly coupled with temperature than with rainfall in KwaZulu-Natal province.

Modelling hydrologic impacts of light absorbing aerosol deposition on snow at the catchment scale

Abstract. Light absorbing impurities in snow and ice (LAISI) originating from atmospheric deposition enhance snowmelt by increasing the absorption of shortwave radiation. The consequences are a shortening of the snow duration due to increased snowmelt and, at the catchment scale, a temporal shift in the discharge generation during the spring melt season. In this study, we present a newly developed snow algorithm for application in hydrological models that allows for an additional class of input variable: the deposition mass flux of various species of light absorbing aerosols. To show the sensitivity of different model parameters, we first use the model as a 1-D point model forced with representative synthetic data and investigate the impact of parameters and variables specific to the algorithm determining the effect of LAISI. We then demonstrate the significance of the radiative forcing by simulating the effect of black carbon (BC) deposited on snow of a remote southern Norwegian catchment over a 6-year period, from September 2006 to August 2012. Our simulations suggest a significant impact of BC in snow on the hydrological cycle. Results show an average increase in discharge of 2.5, 9.9, and 21.4 %, depending on the applied model scenario, over a 2-month period during the spring melt season compared to simulations where radiative forcing from LAISI is not considered. The increase in discharge is followed by a decrease in discharge due to a faster decrease in the catchment's snow-covered fraction and a trend towards earlier melt in the scenarios where radiative forcing from LAISI is applied. Using a reasonable estimate of critical model parameters, the model simulates realistic BC mixing ratios in surface snow with a strong annual cycle, showing increasing surface BC mixing ratios during spring melt as a consequence of melt amplification. However, we further identify large uncertainties in the representation of the surface BC mixing ratio during snowmelt and the subsequent consequences for the snowpack evolution.

Investigation of the Intra-Annual Variability of the North Equatorial Countercurrent/North Brazil Current Eddies and of the Instability Waves of the North Tropical Atlantic Ocean Using Satellite Altimetry and Empirical Mode Decomposition

AbstractThe intra-annual variability of the tropical Atlantic Ocean north of the equator is investigated with satellite altimetry mean sea level anomaly data and with an algorithm based on empirical mode decomposition (EMD) methods. Two regions of high variability are identified. The first region, between 3° and 12°N, is characterized by the presence of westward-propagating eddies linked to the North Brazil Current (NBC) retroflection in the vicinity of the Brazilian coast. They show a strong annual cycle. In this paper the EMD algorithm points out that this signal is frequency modulated shifting from large length-scale structures in October to smaller ones in March. Consequently, the number of “eddies” per year can be aliased, according to the time and location of sampling, and can impact the percentage they explain of the interhemispheric exchange of mass and heat associated with the meridional overturning circulation’s upper limb. A scenario concerning this dynamics is proposed. The second region reveals the presence of westward-propagating instability waves centered north of the equator (3°–7°N) between 50° and 10°W. These instability waves are also frequency modulated and show a strong seasonal cycle with maximum amplitude around August.

Temperature and precipitation in the context of the annual cycle over Asia: Model evaluation and future change

Since the early or late arrival of monsoon rainfall can be devastating to agriculture and economy, the prediction of the onset of monsoon is a very important issue. The Asian monsoon is characterized by a strong annual cycle with rainy summer and dry winter. Nevertheless, most of monsoon studies have focused on the seasonal-mean of temperature and precipitation. The present study aims to evaluate a total of 27 coupled models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) for projection of the time evolution and the intensity of Asian monsoon on the basis of the annual cycle of temperature and precipitation. And future changes of onset, retreat, and intensity of monsoon are analyzed. Four models for good seasonal-mean (GSM) and good harmonic (GH) groups, respectively, are selected. GSM is based on the seasonal-mean of temperature and precipitation in summer and winter, and GH is based on the annual cycle of temperature and precipitation which represents a characteristic of the monsoon. To compare how well the time evolution of the monsoon is simulated in each group, the onset, retreat, and duration of Asian monsoon are examined. The highest pattern correlation coefficient (PCC) of onset, retreat, and duration between the reanalysis data and model outputs demonstrates that GH models’ MME predicts time evolution of monsoon most precisely, with PCC values of 0.80, 0.52, and 0.63, respectively. To predict future changes of the monsoon, the representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2073-2099 are compared with historical simulations for the period of 1979-2005 from CMIP5 using GH models’ MME. The Asian monsoon domain is expanded by 22.6% in the future projection. The onset date in the future is advanced over most parts of Asian monsoon region. The duration of summer Asian monsoon in the future projection will be lengthened by up to 2 pentads over the Asian monsoon region, as a result of advanced onset. The Asian monsoon intensity becomes stronger with the passage of time. This study has important implication for assessment of CMIP5 models in terms of the prediction of time evolution and intensity of Asian monsoon based on the annual cycle of temperature and precipitation.

The seasonality and effects of temperature and rainfall on Campylobacter infections

ABSTRACTBackground Campylobacteriosis is a major public health concern. Despite evidence that climate factors influence the spatio-temporal patterns of the infections; their impact is not fully described and understood.
 ObjectivesTo examine methods for determining the impact of rainfall and temperature on Campylobacter cases in England and Wales.
 MethodsReported cases for England and Wales were linked to local temperature and rainfall at laboratory postcode locations in the 30 days before the specimen date. Descriptive, statistical and spatial methods included a novel Comparative Conditional Incidence (CCI), wavelet analysis, hierarchical clustering, generalized additive model (GAM) and generalized structural time series model (GEST).ResultsThe Campylobacter increase in late spring was linked to temperature two weeks prior, with an increase in CCI of 0.175 cases per 100,000 per week for weeks 17 to 24; the relationship was non-linear and changed through the year. GEST with penalized varying temperature coefficient found 33% of the seasonal change was attributable to temperature, while with a fixed temperature coefficient found 8%. Wavelet analysis showed a strong annual cycle, with harmonics at six and four months and no simple association with temperature or rainfall. Geographic clustering showed three clusters with geographic similarities, representing metropolitan, rural, and other areas.
 ConclusionsOur analyses provide more robust and convincing associations than simple regression analysis. The association with temperature is likely to be indirect and the primary driver remains to be determined. Local-temporal linkage of weather parameters and cases is important in improving the resolution of climate associations with infectious diseases and provides methods which can improve disease predictions. Further examination of data from a wider geographic area and longer time series should improve the understanding of the epidemiology and drivers of human Campylobacter infections.