Winter Variance Research Articles

Role of SST in Seasonal Western North Pacific Anomalous Anticyclone: Insights From AMIP Simulations in CMIP6

AbstractThe western North Pacific anticyclone (WNPAC) significantly influences the East Asian climate and is modulated by tropical sea surface temperature (SST). This study uses 142 AMIP simulations from 33 Coupled Model Intercomparison Project (CMIP6) models to quantify the contributions of SST to the interannual variability of the WNPAC. SST forcing accounts for 66%, 77%, and 49% of the WNPAC variance in winter, spring, and summer, respectively. The persistence of the WNPAC depends on the relaying effects of SST in three tropical oceans. CMIP6 models exhibit excessive precipitation response to the Pacific SST, leading to an overestimated (underestimated) Pacific (Indian Ocean) effect in modulating the summer WNPAC. Sensitivity experiments with an atmospheric model confirm the crucial role of the Pacific in regulating the WNPAC interannual variation and the contribution from the tropical North Atlantic in spring. The tropical Indian Ocean only exerts a minor impact on the WNPAC when excluding the interactions with other oceans.

Spatial correlation in weather forecast accuracy: a functional time series approach

A functional time series approach is proposed for investigating spatial correlation in daily maximum temperature forecast errors for 111 cities spread across the U.S. The modelling of spatial correlation is most fruitful for longer forecast horizons, and becomes less relevant as the forecast horizon shrinks towards zero. For 6-day-ahead forecasts, the functional approach uncovers interpretable regional spatial effects, and captures the higher variance observed in inland cities versus coastal cities, as well as the higher variance observed in mountain and midwest states. The functional approach also naturally handles missing data through modelling a continuum, and can be implemented efficiently by exploiting the sparsity induced by a B-spline basis. The temporal dependence in the data is modeled through temporal dependence in functional basis coefficients. Independent first order autoregressions with generalized autoregressive conditional heteroskedasticity [AR(1)+GARCH(1,1)] and Student-t innovations work well to capture the persistence of basis coefficients over time and the seasonal heteroskedasticity reflecting higher variance in winter. Through exploiting autocorrelation in the basis coefficients, the functional time series approach also yields a method for improving weather forecasts and uncertainty quantification. The resulting method corrects for bias in the weather forecasts, while reducing the error variance.

Seasonal variations in the synoptic climatology of air pollution in Birmingham, UK

A synoptic typing approach was undertaken to examine the seasonal relationship (winter versus summer) between air mass types and pollutant concentrations of O3, PM10, NOx, NO2 and CO in Birmingham, UK, from 2000 to 2015. Daily means of seven surface meteorological variables were entered into a P-mode principal component analysis. Three principal components explained 72.2% (72.9%) of the variance in winter (summer). Cluster analysis was used to group together days with similar PC scores and thus similar meteorological conditions. Six clusters provided the best air mass classification in both seasons. High pollutant concentrations were associated with anticyclonic types. In particular, tropical (polar) continental air mass type was most likely to produce extremely high concentrations in summer (winter). In winter, a sequence of Polar Continental (cool and humid) and Binary Mid-latitude Anticyclonic Maritime—Sub-Polar Cyclonic Maritime (cold and dry) induced severe pollution episodes in all pollutants. Whilst the mean duration of severe pollution episodes varied little between winter and summer (O3 was an exception, with severe episodes lasting 20% longer in summer), high pollutant extremes were more common in winter. This was due to more favourable meteorological conditions (e.g. temperature inversions) and increased anthropogenic emissions during the cold season.

The relative importance of weather and nutrients determining phytoplankton assemblages differs between seasons in large Lake Taihu, China

Climate change affects seasonal weather patterns, but little is known about the consequent effects on phytoplankton assemblage variation. We studied the changes in phytoplankton assemblages, expressed as morpho-functional groups, during four seasons over the past two decades in large shallow eutrophic Lake Taihu, China. During this period, both climate and nutrient levels changed in the lake. Wind speed declined significantly from 1997 to 2016 in all seasons, while global radiation increased significantly in spring and winter. Phosphorus and chlorophyll a concentrations showed a significant increasing trend in all seasons, especially in summer and autumn. Diatoms, mainly Aulacoseira and Asterionella, increased during late winter and early spring. Multiple stepwise regression analysis and non-metric multidimensional scaling indicated that climatic variables (i.e., decreasing wind speed and increasing global radiation) were the main drivers of phytoplankton assemblage variance in winter and early spring. An increase in the dominance of cyanobacteria (mainly Microcystis spp.) in summer and autumn was mainly related to changes in phosphorus. Our results indicate that both nutrients and climatic variables were major drivers of the observed changes in phytoplankton assemblages, differing in importance between seasons. The differential response of phytoplankton community variation to future environmental change in the different seasons needs to be taken into account when evaluating the long-term changes in phytoplankton.

Contribution of atmospheric circulation to recent off-shore sea-level variations in the Baltic Sea and the North Sea

Abstract. The main purpose of this study is to quantify the contribution of atmospheric factors to recent off-shore sea-level variability in the Baltic Sea and the North Sea on interannual timescales. For this purpose, we statistically analysed sea-level records from tide gauges and satellite altimetry and several climatic data sets covering the last century. Previous studies had concluded that the North Atlantic Oscillation (NAO) is the main pattern of atmospheric variability affecting sea level in the Baltic Sea and the North Sea in wintertime. However, we identify a different atmospheric circulation pattern that is more closely connected to sea-level variability than the NAO. This circulation pattern displays a link to sea level that remains stable through the 20th century, in contrast to the much more variable link between sea level and the NAO. We denote this atmospheric variability mode as the Baltic Sea and North Sea Oscillation (BANOS) index. The sea-level pressure (SLP) BANOS pattern displays an SLP dipole with centres of action located over (5° W, 45° N) and (20° E, 70° N) and this is distinct from the standard NAO SLP pattern in wintertime. In summertime, the discrepancy between the SLP BANOS and NAO patterns becomes clearer, with centres of action of the former located over (30° E, 45° N) and (20° E, 60° N). This index has a stronger connection to off-shore sea-level variability in the study area than the NAO in wintertime for the period 1993–2013, explaining locally up to 90 % of the interannual sea-level variance in winter and up to 79 % in summer. The eastern part of the Gulf of Finland is the area where the BANOS index is most sensitive to sea level in wintertime, whereas the Gulf of Riga is the most sensitive region in summertime. In the North Sea region, the maximum sea-level sensitivity to the BANOS pattern is located in the German Bight for both winter and summer seasons. We investigated, and when possible quantified, the contribution of several physical mechanisms which may explain the link between the sea-level variability and the atmospheric pattern described by the BANOS index. These mechanisms include the inverse barometer effect (IBE), freshwater balance, net energy surface flux and wind-induced water transport. We found that the most important mechanism is the IBE in both wintertime and summertime. Assuming a complete equilibration of seasonal sea level to the SLP gradients over this region, the IBE can explain up to 88 % of the sea-level variability attributed to the BANOS index in wintertime and 34 % in summertime. The net energy flux at the surface is found to be an important factor for the variation of sea level, explaining 35 % of sea-level variance in wintertime and a very small amount in summer. The freshwater flux could only explain 27 % of the variability in summertime and a negligible part in winter. In contrast to the NAO, the direct wind forcing associated with the SLP BANOS pattern does not lead to transport of water from the North Sea into the Baltic Sea in wintertime.

Basis for application of new-generation anti-icing materials as an efficient way to reduce the accident rate on roads in winter

Abstract The use of advanced anti-icing materials is important to ensure and maintain the maximum traffic capacity, decrease the accident rate on motor roads exposed to adverse weather conditions in winter. The primary issue in applying these materials deals with ensuring the required traffic safety, therefore, these materials should undergo diagnostics before they can be recommended for use, and, subsequently, the condition of motor roads should be assessed. The diagnostic information obtained allows for comprehensive assessment of road operating conditions representing the most important factor in evaluating road pavement safety, especially in winter. The study addresses the issue of providing the basis for application of anti-icing materials to ensure the required safety on roads in winter. The study is focuses on road pavement operating conditions in winter, and the potential of using the new-generation anti-icing Nordway material and sand-and-salt mixture traditionally used in Russia’s periphery. As a result, due to the use of the new-generation anti-icing material, primary indicators of traffic safety assurance in winter are established. A full-scale experiment using the material under study is performed, primary cohesive properties for the experimental section of the road pavement are determined. Data on the braking distance variance in winter are gathered. A comparative analysis is carried out for a similar data set when using the traditional material, when using the tested material (of new generation) and without applying any materials. The most efficient way to reduce the accident rate on roads in winter using one of the anti-icing materials studied is established.

Identifying Dynamically Induced Variability in Glacier Mass-Balance Records

Abstract Glacier mass balance provides a direct indicator of a glacier’s relationship with local climate, but internally generated variability in atmospheric circulation adds a significant degree of noise to mass-balance time series, making it difficult to correctly identify and interpret trends. This study applies “dynamical adjustment” to seasonal mass-balance records to identify and remove the component of variance in these time series that is associated with large-scale circulation fluctuations (dynamical adjustment refers here to a statistical method and not a glacier’s dynamical response to climate). Mass-balance records are investigated for three glaciers: Wolverine and Gulkana in Alaska and South Cascade in Washington. North Pacific sea level pressure and sea surface temperature fields perform comparably as predictors, each explaining 50%–60% of variance in winter balance and 25%–35% in summer balance for South Cascade and Wolverine Glaciers. Gulkana Glacier, located farther inland, is less closely linked to North Pacific climate variability, with the predictors explaining roughly 30% of variance in winter and summer balance. To investigate the degree to which this variability affects trends, adjusted mass-balance time series are compared to those in the raw data, with common results for all three glaciers; winter balance trends are not significant initially and do not gain robust significance after adjustment despite the large amount of circulation-related variability. However, the raw summer balance data have statistically significant negative trends that remain after dynamical adjustment. This indicates that these trends of increasing ablation in recent decades are not due to circulation anomalies and are consistent with anthropogenic warming.

Interannual variability of Mediterranean evaporation and its relation to regional climate

Gridded monthly evaporation data for 1958–2006 from the Woods Hole Oceanographic Institution data set are used to investigate interannual variability of Mediterranean evaporation during cold and hot seasons and its relation to regional atmospheric dynamics, sea surface temperature and atmospheric elements of the hydrological cycle. The first EOF mode of Mediterranean evaporation, explaining more than 50% of its total variance, is characterized by the monopole pattern both in winter and summer. However, despite structural similarity, the EOF-1 of Mediterranean evaporation is affected by different climate signals in cold and hot seasons. During winter the EOF-1 is associated with the East Atlantic teleconnection pattern. In summer, there is indication of tropical influence on the EOF-1 of Mediterranean evaporation (presumably from Asian monsoon). Both in winter and summer, principal components of EOF-1 demonstrate clear interdecadal signals (with a stronger signature in summer) associated with large sea surface temperature anomalies. The results of a sensitivity analysis suggest that in winter both the meridional wind and the vertical gradient of saturation specific humidity (GSSH) near the sea surface contribute to the interdecadal evaporation signal. In summer, however, it is likely that the signal is more related to GSSH. Our analysis did not reveal significant links between the Mediterranean evaporation and the North Atlantic Oscillation in any season. The EOF-2 of evaporation accounts for 20% (11%) of its total variance in winter (in summer). Both in winter and summer the EOF-2 is characterized by a zonal dipole with opposite variations of evaporation in western and eastern parts of the Mediterranean Sea. This mode is associated presumably with smaller scale (i.e., local) effects of atmospheric dynamics. Seasonality of the leading modes of the Mediterranean evaporation is also clearly seen in the character of their links to atmospheric elements of the regional hydrological cycle. In particular, significant links to precipitation in some regions have been found in winter, but not in summer.

TEMPERATURE VARIABILITY AND LONG-TERM SURVIVAL

Background and Aims: Time series studies show that cold and hot temperatures, and their extremes, are associated with increased death rates. Few if any studies have evaluated longer-term temperature associations with deaths. Because there is evidence of adaptation to usual temperature, but higher deaths at unusual temperatures, we hypothesized that a long-term exposure relevant to mortality might be temperature variability. We investigated whether the variance of summer (June-August) and winter (December-February) temperatures were associated with survival in four cohorts of persons with predisposing diseases in 135 US cities. Rather than modeling exposure cross-sectionally, as typical in cohort studies, we treated temperature variance as a time varying exposure. Methods: We used Medicare data (1985-2006), and constructed cohorts of persons hospitalized with: chronic obstructive pulmonary disease (COPD), diabetes, congestive heart failure (CHF), and myocardial infarction (MI). Yearly summer and winter temperature variance were linked to the individuals during follow up in each city. We applied Cox’s proportional hazard model for each cohort within each city, adjusting for individual risk factors, and long term trends, and pooled results across cities. Results: Significant summer hazard ratios for mortality, ranged from 1.038 (95% Confidence Interval (CI): 1.024, 1.052) per an IQR increase in summer variance for persons with CHF, to 1.055 (95% CI: 1.035, 1.076) for persons with an MI. Associations during winter were also significant, with a hazard ratio of 1.017 (95% CI: 1.009, 1.025) for CHF, and 1.018 (95% CI: 1.008, 1.028) for persons with MI, per IQR increase in winter variance. Associations were higher in the elderly and lower in cities with a higher percent of green space. Conclusions: Increases in temperature variability in the cold and warm seasons were associated with increased mortality of the elderly. Some adaptation measures, such as green space, may ameliorate this effect.

Gravity wave–tidal interactions in the mesosphere and lower thermosphere over Rothera, Antarctica (68°S, 68°W)

A simple technique for measuring gravity wave activity has been used to investigate gravity wave–tidal interactions in the polar mesosphere and lower thermosphere (MLT). The technique uses the radial velocities of individual meteors recorded by meteor radar to derive a statistical measure (variance) of the activity of the high‐frequency gravity wave field. This technique can measure gravity waves with horizontal wavelengths of up to about 400 km and periods up to approximately 3 hours. Interactions between the observed gravity wave field and the background wind are investigated using data collected between February 2005 and December 2008 by a meteor radar based at Rothera, Antarctica (68°S, 68°W). The results reveal the presence of significant modulations of the observed gravity wave field at tidal periods of 12 and 24 hours. Correlations between the hourly zonal winds and the gravity wave field measured by the meteor radar reveal an in‐phase relationship between the hourly zonal winds and gravity wave variance in winter and an anti‐phase relationship in summer. This is consistent with the theory of filtering by tidal winds acting on a zonally‐asymmetric gravity wave field in which westward waves dominate in winter and eastward waves dominate in summer. The limitations of the technique and the effect this has on the interpretation of these results are also considered. The effects of the diurnal cycles in meteor count rates, the uncertainty in recorded radial velocities and the uncertainty in the measured heights of meteors are considered.

Arctic Oscillation influence on daily temperature variance in winter over China

The relationship between the Arctic Oscillation (AO) and daily temperature variance of 150 Chinese stations are investigated in the present study for wintertime (1November through 31 March) in the period of 1954–2001. Results show that the temperature variance significantly decreases during the high AO years, and increases in low AO cases. A key factor connecting them is the Siberian High, particularly the high-frequency fluctuations of the High. Within the seasonal time scale, the frequency of low-temperature extremes (daily temperature anomaly below −2σ, σ is the standard deviation of daily temperature for a given winter and a given station) displays an odd relation to the variance: a larger (smaller) variance is found to be associated with smaller (greater) frequency of low-temperature events. That is due to the non-normal distribution of the temperatures, and also influenced by the phases of AO. During the last 50 years or so, AO experiences a significant increasing trend, meanwhile the variance of daily sea level pressure (SLP) in the central region of Siberian High has decreased at a rate of −10.7%/10 a. These result in a significant weakening of the daily temperature variance in China with a trend of −4.1%/10 a, and a significant increase in the intra-seasonal low-temperature extremes at a rate of 0.16d/10 a.

Statistical Tests for Comparison of Daily Variability in Observed and Simulated Climates

Abstract Tests for differences in daily variability based on the jackknife are presented. These tests properly account for the effect of autocorrelation in the data and are reasonably robust against departures from normality. Three measures for the daily variability are considered: process, within-month, and innovation variance. The jackknife statistic compares the logarithm of these measures. The standard errors of this logarithm are obtained by recomputing the variance estimates for all subsamples wherein one month is omitted from the complete simple. A simple extension of the jackknife procedure is given to obtain a powerful multivariate test in situations that the differences in variance have the same sign across the region considered or over the year. As an illustration the tests are applied to near-surface temperatures over Europe simulated by the coupled ECHAM/LSG model. It is shown that the control run of the model significantly overestimates the process variance in winter and spring and the withi...

Empirical Orthogonal Function Analysis of Hawaiian Rainfall

Abstract Empirical orthogonal function analysis was applied to monthly mean rainfall data at 63 stations in Hawaii encompassing a 37-year period. Major rainfall patterns in order to importance (E1–E3) proved to be trade wind, southwest wind and convective rainfall on an annual basis; trade wind, southwest wind and frontal rainfall during winter, spring and fall seasons; and trade wind, tropical disturbance and convective rainfall during summer. Trade wind rainfall (E1) explains most rainfall variance in summer and least variance in winter. Spectral analyses of the time-dependent coefficients for eigenvectors E1–E5 show annual, semi-annual, three-forths year, and 2–2½ year cycles. No spectral peaks relating to the 11- and 22-year sunspot cycles were found. Composite rainfall maps for wet and dry winter and summer half-years indicate the contributions that specific eigenvector patterns make to these anomalies. Comparisons between Hawaiian rainfall and E1 Ninos reveal that most (not all) E1 Nino winters in H...