Large-scale Atmospheric Circulation Indices Research Articles

Hymenaea stignocarpa Mart. ex Hayne growth–climate relationships are regulated by soil water saturation in Cerrado-Pantanal ecotone

The expected intensification of the dry season, and concentration of rainfall during the wet season, can disrupt tree growth and regional biodiversity in the Cerrado-Pantanal transition zone. Thus, this study aims to assess the climatic responses of Hymenaea stigonocarpa tree growth, a common tree species in this region. Incremental cores were collected at breast height (ca. 1.3 m) from 67 trees to construct a dendrochronological series to correlate annual growth with local meteorological variables and large-scale atmospheric circulation indices from the Pacific and Atlantic Oceans. Significant positive correlations were observed between tree growth and the Pacific Ocean indices. Maximum and average air temperatures of the previous dry season negatively influenced growth, while precipitation at the beginning of the growth season (November) positively influenced growth. Tree growth was not correlated with temperature or rainfall during the wet season. However, at the end of the wet season (February), tree growth was negatively correlated with air temperature and positively correlated with rainfall, but the relationship shifted in the next month (March) suggesting that soil water saturation reduced growth. Our results indicate that dendrochronological studies of H. stignocarpa are useful for assessing the environmental change on the Cerrado-Pantanal ecotone. Furthermore, variations in water availability and temperature associated with changes in large-scale oceanic circulation and local meteorological conditions will impact the growth dynamics of this important Cerrado tree species.

Nonstationary frequency analysis and uncertainty quantification for extreme low lake levels in a large river-lake-catchment system

Extreme hydrological events have become increasingly frequent on a global scale. The middle Yangtze River also faces a substantial challenge in dealing with extreme flooding and drought. However, the long-term characteristics of the extreme hydrological regime have not yet been adequately recognized. Moreover, there is uncertainty in the extreme value estimation, and this uncertainty needs to be distinguished and quantified. In this study, we investigated the nonstationary frequency characteristics of extreme low lake levels (ELLLs), taking the Poyang Lake as an example. Daily lake levels from 1960 to 2022 were utilized to estimate the return level using the generalized Pareto distribution (GPD). The uncertainty from three sources, i.e., the parameter estimator, threshold selection, and covariate, was quantified via variance decomposition. The results indicate that (1) the parameter estimator is the predominant source of uncertainty, with a contribution rate of approximately 87 %. The total uncertainty of the covariate, threshold, and interaction term is only 13 %. (2) Two indexes, namely the annual minimum water level (WLmin) and the days with peak over the 90 % threshold per year (DPOT90), decreased (0.01–0.03 m/year) and increased (0.17–1.39 days/year), respectively, indicating a progressively severe drought trend for Poyang Lake. (3) The return level with return period of 5 to 100 years significantly decreased after the early 21st century. A large spatial heterogeneity was identified for the variation in the return level, and the change rate of the return level with a 100-year return period ranged from 5 % to 40 % for the whole lake. (4) The ELLLs had a stronger correlation with the catchment discharge than with the Yangtze River discharge and the large-scale atmospheric circulation indices. This study provides a methodology with reduced uncertainty for nonstationary frequency analysis (NFA) of ELLLs exemplified in large river–lake systems.

Spatiotemporal variability of rainfall erosivity and its teleconnection with atmospheric circulation in monsoon-driven climate region

Understanding the spatiotemporal variability of annual, monthly, and seasonal rainfall erosivity (RE) is crucial for determining the risk of soil erosion and developing soil conservation plans. However, little knowledge is available on RE at the monthly, seasonal, and annual scales in monsoon-driven climate regions like Bangladesh. Therefore, we aimed to assess the spatiotemporal variability of RE in Bangladesh from 1980 to 2017 and analyze teleconnection of RE with large-scale atmospheric circulation indices. The detrended fluctuation analysis (DFA) and cross wavelet analysis were employed to evaluate the potential future trends and interpret the periodic cycles in the RE, respectively. The results demonstrate that mean annual RE values fluctuated from 12574.16 MJ.mm.ha-1.h-1 to 123914.76 MJ.mm.ha-1.h-1, while RE has been lower in recent decades than in the earlier decades. The mean annual RE is decreasing all over the country, and significant abrupt change points occurred in the early 2000 s. The highest mean annual RE was observed in the southernmost part of Bangladesh and the lowest in the western part of the country. The results of DFA indicated that the RE trend would sustain its present trend in the upcoming period, except for May and July. The effects of Niño3.4 SST and IOD, SASMI, and EASMI have almost no to minimal influence on the RE trend in Bangladesh. However, a noticeable impact was found on the monthly scale, which could be why the observed intra-annual variability of RE was observed. We found that the average RE has reduced significantly with increasing distance from the sea, latitude, and elevation in Bangladesh. The study found that increasing geopotential height in the summer and decreasing geopotential height in the winter with enough moisture divergence, decreasing convective precipitation, decreasing large-scale rain rate, decreasing specific cloud liquid water content, and decreasing explicit rainwater content all contributed to RE variability and change in the country.

Rice yield responses in Bangladesh to large-scale atmospheric oscillation using multifactorial model

This paper intends to explore rice yield fluctuations to large-scale atmospheric circulation indices (LACIs) in Bangladesh. The annual dataset of climate-derived yield index (CDYI), estimated using principal component analysis of Aus rice yield data of 23 districts, and five LACIs for the period 1980–2017 were used for this purpose. The key outcomes of the study were as follows: three sub-regions of Bangladesh, northern, northwestern, and northeastern, showed different kinds of CDYI anomalies. The CDYI time series in north and northeastern regions exhibited a substantial 6-year fluctuation, whereas a 2.75- to 3-year fluctuation predominated the northwestern region. Rice yield showed the highest sensitivity of LACIs in the northern region. Indian Ocean dipole (IOD) and East Central Tropical Pacific SST (Nino 3.4) in July and IOD index in March provide the best yield prediction signals for northern, northwestern, and northeastern regions. Wavelet coherence study demonstrated significant in-phase and out-phases coherences between vital climatic variables (KCVs) and CDYI anomalies at various time-frequencies in three sub-regions. The random forest (RF) model revealed the IOD as the crucial contributing factor of rice yield fluctuations in the country. The multifactorial model with different LACIs and year as predictors can predict rice yield, with the mean relative error (MRE) in the range of 4.82 to 5.78% only. The generated knowledge can be used to early assess rice yield and recommend policy directives to ensure food security.

Responses of yield variability of summer maize in Henan province, north China, to large-scale atmospheric circulation anomalies

Based on the climate-driven yield index (CDYI) series of summer maize in 17 cities and the monthly series of large-scale atmospheric circulation indices (LACI), the responses of yield fluctuations of summer maize to atmospheric circulation anomalies during 1988–2017 were explored in Henan province, north China. The main findings were as follows: (1) with using principal component analysis, east, north, central, and west Henan were identified as four sub-regions with different CDYI variations; (2) with using ensemble empirical mode decomposition, the CDYI in east and north Henan presented a notable 6-year oscillation, while central and west Henan were dominated by a 3-year oscillation; (3) East Pacific/North Pacific Oscillation in January, Eastern Tropical Pacific SST in May, Tropical Southern Atlantic Index in June, and North Pacific in September were the optimal yield prediction signals in east, north, central, and west Henan, respectively; (4) the regression model with predictors as year and various LACI had the ideal forecasting results on actual regional maize yield, with the average relative error ranged from 4.94 to 9.20%.

Climate-driven Yield Variability for Winter Wheat in Henan Province, North China and its Relation to Large-scale Atmospheric Circulation Indices

The responses of wheat yield to large-scale atmospheric circulation indices (LACI) were explored in Henan province, north China. With using the annual series of climate-driven yield index (CDYI) extracted from winter wheat yield collected in 17 cites and the monthly series of 15 types of LACI during 1988–2017, the main findings were as follows: (1) this province could be divided into four sub-regions (central-east, west, north, and south Henan) with different CDYI variations; (2) the CDYI in central-east, west, south Henan was dominated by a 3-year oscillation, while the CDYI in north Henan presented a notable 7.5-year oscillation; (3) among the four sub-regions, central-east Henan had the most significant CDYI-LACI relationship, and the higher Nino 1 + 2 in December were a key yield reduction signal; (4) during 2008–2017, the stronger increase of Nino1 + 2_in December had caused the yield decrease in central Henan by 6.58%. In summary, linking wheat yield to LACI anomalies should be instrumental in alleviating the adverse effects of climate change on wheat production.

Advection pathways at the Mt. Cimone WMO-GAW station: Seasonality, trends, and influence on atmospheric composition

Relationships are analysed between advection pathways and atmospheric composition at the high-mountain station of Mt. Cimone (Italy), between 1998 and 2011. Back-trajectory cluster analysis identifies eight main advection pathways. A connection is demonstrated between the seasonality of airmass transport and atmospheric composition. Temporal trends and correlation of variables, flow types and teleconnection indices show, among other, decreasing trends of 210 Pb (a radionuclide of crustal origin; −0.008 mBq m −3 year −1 ) as well as PM 10 (−0.15 μg m −3 year −1 ), indicating that previously observed downward PM 10 trends in Europe may actually be attributable to a combination of meteorological factors and decreasing anthropogenic emissions. The detection of a positive (negative) correlation of these tracers with Western (Arctic) air masses, showing significant downward (upward) trends at the study site, further confirms our findings. Lastly, relationships between teleconnection indices and atmospheric transport types/atmospheric variables are further analysed, focusing on large-scale atmospheric circulation indices and regional low-frequency atmospheric circulation pathways, the Mediterranean Oscillation and the Western Mediterranean Oscillation. The analysis reveals the important influence of such regional indices on the advection pathways. • Characterisation of primary advection pathways to the Mt. Cimone baseline station. • Characterisation of atmospheric constituents by advection pathway to Mt. Cimone. • Trend analysis of atmospheric pathways and atmospheric composition at Mt. Cimone. • Associations between pathways, atmospheric composition and teleconnection indices.

Monthly precipitation assessments in association with atmospheric circulation indices by using tree-based models

The Urmia Lake basin is one of the most important basins in Iran, facing many problems due to poor water management and rainfall reduction. Under current circumstances, it becomes critical to have an advanced understanding of rainfall patterns in the basin, setting the motivation of this study. In this research, the mean monthly meteorological data of six synoptic stations of Urmia Lake basin were used (including relative humidity, temperature, minimum–maximum temperature and pressure) and large-scale atmospheric circulation indices (Southern Oscillation Index, North Atlantic Oscillation, Western Mediterranean Oscillation, Mediterranean Oscillation-Gibraltar/Israel and Mediterranean Oscillation-Algiers/Cairo) and sea surface temperatures of the Mediterranean, Black, Caspian, Red seas and Persian Gulf in the period 1988–2016. Various combinations of these variables used as input to the M5 tree and random forest models were selected by Relief algorithm for each month in three scenarios including atmospheric circulation indices, meteorological variables and combination of both. After the implementation of two models with three different scenarios, the evaluation criteria including correlation coefficient (R), mean absolute error and root-mean-square error were calculated and the Taylor diagram for each model was plotted. Our results showed that the M5 tree model performed superior in January, February, March, April, June, September, November and December, while the random forest model did in the remaining months. In addition, the indications of this study showed that the combination of atmospheric circulation indices and meteorological variables used as input to the models mostly constituted improved results.

Multiscale variability of streamflow in the Three Rivers Headwater Region, China, and links to large-scale atmospheric circulation indices

Abstract Exploring the relations between streamflow and large-scale atmospheric circulation systems can assist in identifying potentially useful indicators for the modeling of hydrological processes. With the help of ensemble empirical mode decomposition and the wavelet analysis method, this research explored streamflow variations and its links to large-scale atmospheric circulation indices during 1960–2012 in the Three Rivers Headwater Region (TRHR). A steady increasing trend was detected in the streamflow of the source region of Yangtze River (SYR), and a steady decreasing trend was detected in the streamflow of the source region of Lancang River (SLR). The streamflow of the source region of Yellow River (SYeR) had an increasing trend in the early years of the study period and subsequently exhibited a decreasing trend. The Tibetan Plateau monsoon (TPM), Arctic Oscillation (AO), and South Asia monsoon (SAM) are the key factors influencing streamflow changes in the SYR, SYeR, and SLR, respectively. At interannual time-scale variation with the period of about 3–9 years, an antiphase relationship exists between SYR streamflow and TPM indices, while in-phase relationships are detected between SYeR (SLR) streamflow and AO (SAM) indices.

Evidence of climate shift for temperature and precipitation extremes across Gansu Province in China

Temperature and precipitation extremes are the dominant causes of natural disasters. In this study, seven indices of extreme temperature and precipitation events in Gansu Province, China, were analysed for the period 1961–2017. An abrupt climate shift was recorded during 1980–1981. Thus, the study period was divided into a preshift (before the climate shift) period 1961–1980 and an aftshift (after the climate shift) period 1981–2017. Comparison of mean extreme indices for preshift and aftshift periods was performed for the purpose of exploring possible increasing/decreasing patterns. Generalized extreme value (GEV) distribution was applied spatially to fit the extreme indices with return periods up to 100 years for preshift/aftshift periods. Singular value decomposition (SVD) was adopted to investigate possible correlation between the extreme climate events and indices of large-scale atmospheric circulation. The results indicate that changes in mean and return levels between the preshift and aftshift periods vary significantly in time and space for different extreme indices. Increase in extreme temperature regarding magnitude and frequency for the aftshift period as compared with the preshift period suggests a change to a warmer and more extreme climate during recent years. Changes in precipitation extremes were different in southern and northern parts of Gansu. The precipitation extremes in the north have increased that can result in more serious floods and droughts in the future. SVD analyses revealed a complex pattern of correlation between climate extremes and indices of large-scale atmospheric circulation. Strengthening of westerlies and weakening of the south summer monsoon contribute to the complex changing patterns of precipitation extremes. Results in this study will contribute to disaster risk prevention and better water management in this area.

Spatial and Temporal Variability in the Precipitation Concentration in the Upper Reaches of the Hongshui River Basin, Southwestern China

The statistical characteristics of precipitation play important roles not only in flood and drought risk assessments but also in water resource management. This paper implements a statistical analysis to study the spatial and temporal variability in precipitation in the upper reaches of the Hongshui River basin (UHRB), southwestern China, by analysing time series of daily precipitation from 18 weather stations during the period of 1959 to 2015. To detect precipitation concentrations and the associated patterns, three indices, the precipitation concentration index (PCI), precipitation concentration degree (PCD), and precipitation concentration period (PCP), were used. The relationships between the precipitation concentration indices (PCI, PCD, and PCP) and geographic variables (latitude, longitude, and elevation), large-scale atmospheric circulation indices, and summer monsoon indices were investigated to identify specific dependencies and spatial patterns in the precipitation distribution and concentration. The results show that high PCI values were mainly observed in the northeastern portion of the basin, whereas low PCI values were mainly detected in the southwest. The Mann-Kendall test results demonstrate that the majority of the UHRB is characterized by nonsignificant trends in the PCI, PCD, and PCP from 1959 to 2015. The PCP results reveal that rainfall in the UHRB mainly occurs in summer months, and the rainy season arrives earlier in the eastern UHRB than in the western UHRB. Additionally, the PCD results indicate that the rainfall in the western UHRB is more dispersed throughout the year than that in the eastern UHRB. Compared with other geographical factors, longitude is the most important variable that governs the spatial distribution and variations in annual precipitation and the precipitation concentration indices. Due to a combination of topography, the Indian subtropical high, and monsoon weakening, precipitation may be more concentrated in one period, especially in the eastern part of the basin, which increases the risk of drought.

Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.

Changes in extreme temperature and precipitation events in the Loess Plateau (China) during 1960–2013 under global warming

In recent decades, extreme climatic events have been a major issue worldwide. Regional assessments on various climates and geographic regions are needed for understanding uncertainties in extreme events' responses to global warming. The objective of this study was to assess the annual and decadal trends in 12 extreme temperature and 10 extreme precipitation indices in terms of intensity, frequency, and duration over the Loess Plateau during 1960–2013. The results indicated that the regionally averaged trends in temperature extremes were consistent with global warming. The occurrence of warm extremes, including summer days (SU), tropical nights (TR), warm days (TX90), and nights (TN90) and a warm spell duration indicator (WSDI), increased by 2.76 (P<0.01), 1.24 (P<0.01), 2.60 (P=0.0003), 3.41 (P<0.01), and 0.68 (P=0.0041) days/decade during the period of 1960–2013, particularly, sharp increases in these indices occurred in 1985–2000. Over the same period, the occurrence of cold extremes, including frost days (FD), ice days (ID), cold days (TX10) and nights (TN10), and a cold spell duration indicator (CSDI) exhibited decreases of −3.22 (P<0.01), −2.21 (P=0.0028), −2.71 (P=0.0028), −4.31 (P<0.01), and −0.69 (P=0.0951) days/decade, respectively. Moreover, extreme warm events in most regions tended to increase while cold indices tended to decrease in the Loess Plateau, but the trend magnitudes of cold extremes were greater than those of warm extremes. The growing season (GSL) in the Loess Plateau was lengthened at a rate of 3.16days/decade (P<0.01). Diurnal temperature range (DTR) declined at a rate of −0.06°C /decade (P=0.0931). Regarding the precipitation indices, the annual total precipitation (PRCPTOT) showed no obvious trends (P=0.7828). The regionally averaged daily rainfall intensity (SDII) exhibited significant decreases (−0.14mm/day/decade, P=0.0158), whereas consecutive dry days (CDD) significantly increased (1.96days/decade, P=0.0001) during 1960–2013. Most of stations with significant changes in SDII and CDD occurred in central and southeastern Loess Plateau. However, the changes in days of erosive rainfall, heavy rain, rainstorm, maximum 5-day precipitation, and very-wet-day and extremely wet-day precipitation were not significant. Large-scale atmospheric circulation indices, such as the Western Pacific Subtropical High Intensity Index (WPSHII) and Arctic Oscillation (AO), strongly influences warm/cold extremes and contributes significantly to climate changes in the Loess Plateau. The enhanced geopotential height over the Eurasian continent and increase in water vapor divergence in the rainy season have contributed to the changes of the rapid warming and consecutive drying in the Loess Plateau.

Annual floods in New England (USA) and Atlantic Canada: synoptic climatology and generating mechanisms

New England and Atlantic Canada are characterized by mixed flood regimes that reflect different storm types, antecedent land surface conditions, and flood seasonality. Mixed flood regimes are known to complicate flood risk analyses, yet the synoptic climatology and precipitation mechanisms that generate annual floods in this region have not been described in detail. We analyzed a set of long-term annual flood records at climate-sensitive stream gauges across the region and classified the synoptic climatology of each annual flood, quantitatively describing the precipitation mechanisms, and characterize flood seasonality. We find that annual floods here are dominantly generated by Great Lakes-sourced storms and Coastal lows, known locally as ‘nor’easters.’ Great Lakes storms tend to be associated with lower magnitude annual floods (<75th percentile) and Coastal lows are more clearly associated with higher magnitude events (>75th percentile). Tropical cyclones account for few of all annual floods, including extreme events, despite causing some of the region’s largest and most destructive floods. Late winter/early spring is when the greatest number of annual floods occur region wide, and rainfall is the dominant flood-producing mechanism. Rainfall in combination with snowmelt is also important. Both mechanisms are expected to be impacted by projected regional climate change. We find little evidence for associations between flood-producing synoptic storm types or precipitation mechanisms and large-scale atmospheric circulation indices or time periods, despite upward trends in New England annual flood magnitudes. To more completely investigate such associations, partial duration flood series that include more floods than just the largest of each year, and their associated synoptic climatologies and precipitation mechanisms, should be analyzed.

Frost-free season lengthening and its potential cause in the Tibetan Plateau from 1960 to 2010

Frost-free season was an important index for extreme temperature, which was widely discussed in agriculture and applied meteorology research. The frost-free season changed, which was associated with global warming in the past few decades. In this study, the changes in three indices (the last frost day in spring, the first frost day in autumn, and the frost-free season length) of the frost-free season were investigated at 73 meteorological stations in the Tibetan Plateau from 1960 to 2010. Results showed that the last frost day in spring occurred earlier, significantly in 39 % of the 73 stations. For the regional average, the last frost day in spring occurred earlier, significantly at the rate of 1.9 days/decade during the last 50 years. The first frost day in autumn occurred later, significantly in 31 % of the stations, and the regional average rate was 1.5 days/decade from 1960 to 2010. The changing rate of the first frost day in autumn below 3,000 m was 1.8 times larger than the changing rate above 3,000 m. In addition, the first frost day in autumn above 3,000 m fluctuated dramatically before the early 1990s and then it was later sharply after the early 1990s. The frost-free season length increased significantly at almost all stations in the Tibetan Plateau from 1960 to 2010. For the regional average, the frost-free season lengthened at the rate of 3.1 days/decade. The changing rate of the frost-free season length below 3,000 m was more significant than the changing rate above 3,000 m. Eight indices of large-scale atmospheric circulation were employed to investigate the potential cause of the frost-free season length change in the Tibetan Plateau during the past 50 years. There was a significant relationship between the frost-free season length and the Northern Hemisphere Polar Vortex indices. The weakening cold atmospheric circulation might be an essential factor to the Tibetan Plateau warming since 1960.

Variability of large-scale atmospheric circulation indices for the northern hemisphere during the past 100 years

We present an analysis of the large-scale atmospheric circulation variability since 1900 based on various circulation indices. They represent the main features of the zonal mean circulation in the northern hemisphere in boreal winter (such as the Hadley circulation, the subtropical jet, and the polar vortex in the lower stratosphere) as well as aspects of the regional and large-scale circulation (the Walker Circulation, the Indian monsoon, the North Atlantic Oscillation, NAO, and the North American pattern, PNA). For the past decades we calculate the indices from different reanalyses (NCEP/NCAR, ERA-40, JRA-25, ERA- Interim). For the first half of the 20 th century the indices are statistically reconstructed based on historical upper-air and surface data as well as calculated from the Century Reanalysis. The indices from these observation-based data sets are compared to indices calculated from a 9-member ensemble of all forcings simulations performed with the chemistry-climate model SOCOL. After discussing the agreement among different data products, we analyse the interannual-to-decadal variability of the indices in the context of possible driving factors, such as El Nino/Southern Oscillation (ENSO), volcanic eruptions, and solar activity. The interannual variability of the Hadley cell strength, the subtropical jet strength, or the PNA is well reproduced by the model ensemble mean, i.e., it is predictable in the context of the specified forcings. The source of this predictability is mainly related to ENSO (or more generally, tropical sea-surface temperatures). For other indices such as the strength of the stratospheric polar vortex, the NAO, or the poleward extent of the Hadley cell the correlations between observations and model ensemble mean are much lower, but so are the correlations within the model ensemble. Multidecadal variability and trends in the individual series are discussed in the context of the underlying anthropogenic and natural forcings. While consistent trends were found for some of the indices, results also indicate that care should be taken when analysing trends in reconstructions or reanalysis data. Zusammenfassung Diese Studie prasentiert Ergebnisse einer Analyse der Variabilitat der grosraumigen, atmospharischen Zirkulation seit 1900, basierend auf verschiedenen Zirkulationsindizes. Die Indizes umfassen sowohl die Hauptcharakteristika der zonal gemittelten, nordhemispharischen Zirkulation im Nordwinter (z.B. Hadley- Zirkulation, Subtropenjet und polarer Vortex in der unteren Stratosphare) als auch Aspekte der regionalen und grosraumigen Zirkulation (pazifische Walker-Zirkulation, indischer Monsun, nordatlantische Oszilla- tion (NAO) und das Pacific North American-Muster (PNA)). Die Indizes wurden fur die letzten Dekaden aus verschiedenen Reanalysen berechnet (NCEP/NCAR, ERA-40, JRA-25, ERA-Interim). Fur die erste Halfte des 20. Jahrhunderts wurden sie dagegen, basierend auf historischen Bodendaten und Messdaten aus der freien Troposphare, statistisch rekonstruiert und zusatzlich aus der Twentieth Century-Reanalyse berechnet. All diese auf Messungen basierenden Indizeszeitreihen werden in der vorliegenden Studie mit entsprechenden, aus einem Ensemble von 9 Simulationen gewonnenen Indizeszeitreihen verglichen (alle ex- ternen Forcings aktiviert, Chemie-Klimamodell SOCOL). Nach der genaueren Betrachtung des Grades der ¨ Ubereinstimmung zwischen den verschiedenen Produkten wird die interannuelle und dekadale Vari- abilitat der Indizes im Kontext moglicher Einflussfaktoren wie El Nino/Southern Oscillation (ENSO), Vulkanausbruchen und Sonnenaktivitat analysiert. Die interannuelle Variabilitat der Hadleyzellstarke, des Subtropenjets oder des PNA-Musters wird vom Ensemblemittel des Modells erfolgreich reproduziert, d.h. sie ist vorhersagbar bei Kenntnis der spezifischen Forcings. Die Quelle der Vorhersagbarkeit liegt im Wesentlichen in der ENSO-Variabilitat. Fur andere Indizes wie die Starke des stratospharischen, po- laren Vortex, die NAO oder die polwartige Ausdehnung der Hadleyzelle sind die Korrelationen zwischen Beobachtungen und dem Ensemblemittel des Modells viel kleiner. Dasselbe gilt aber gleichermasen fur die Korrelationen innerhalb des Ensembles. Multidekadale Variabilitat und Trends in den Zeitreihen werden im Zusammenhang mit zugrunde liegenden anthropogenen als auch naturlichen Antriebsfaktoren besprochen. Obwohl fur einige Indizes konsistente Trends gefunden werden konnten, zeigen die Ergeb- nisse auch, dass beim Ableiten von Trends aus Reanalyse- oder Rekonstruktionsdaten Vorsicht geboten ist.

Proxy data reconstructions of the Storglaciären (Sweden) mass-balance record back to AD 1500 on annual to decadal timescales

AbstractRegional summer temperatures (TS), derived from tree rings, and large-scale atmospheric circulation indices (North Atlantic Oscillation (NAO)) were used to infer the mass balance of Storglaciären, Sweden, on annual and decadal timescales back to AD 1500. Winter (January–March) NAO was not a suitable proxy for interannual winter balance variability, but seemed to have substantial influence on decadal timescales. TS were highly correlated to the summer balance, but also to the annual net balance. This association was much weaker on decadal timescales, mainly because of the increased maritime climate around 1980. Storglaciären net balance was modelled back to AD 1500 with annual resolution (using TS as a predictor), and AD 1664 with decadal resolution (using TS and NAO as predictors). Both reconstructions displayed similar evolution. Negative mass balances dominated most of the 16th century, followed by a longer period of predominantly positive mass-balance years culminating in about 1750. This is in agreement with previous suggestions of Holocene maximum expansion of Storglaciären at that time. Subsequently, the mass balance is highly variable, with an increased number of negative years. The build-up to the well-documented early-20th-century advance is evident as mass balance becomes progressively more positive towards the early 20th century.

Assessment of streamflow variability modes in Turkey: 1964–1994

The systematic modes of spatial and temporal variation in 372-month records of streamflow in Turkey are defined using the principal components (PCs) analysis. The PCs were computed from a matrix of monthly records of 78 stations during the period 1964–1994. The analysis revealed not only basic streamflow anomaly patterns but described also the variation of those patterns through time. For this purpose, the map patterns and time series of each PC scores were obtained, but only the first five significant components were selected for further analysis. They accounted for more than 70% of the total variance of the original streamflow data set. Temporal variations of the five PC scores appeared to be fairly synchronous with regional precipitation anomaly patterns documented earlier. Seasonal correlations between the PC scores and the indices of large-scale atmospheric circulation (i.e. the North Atlantic Oscillation (NAO) and the Southern Oscillation (SO)) were computed to infer the physical meaning of the components. For example, using annual and winter average series, the maximum correlation coefficients between the first PC and the NAO and SO indices were found as −0.491 and −0.506 (significant at the 99% level), respectively. This implies the sensibility of the Turkish streamflow climatology to the variations of the NAO. The fifth PC was also shown to be in a significant relation with the SO. Similar analysis was seasonally carried out for the series of precipitation-streamflow PC scores. As a result, the relationships between the series of precipitation-streamflow and precipitation-first PC were fairly strong with a correlation value of 0.657 and 0.596 at the 99.9% significance level, respectively.

Statistical downscaling based on dynamically downscaled predictors: Application to monthly precipitation in Sweden

A prerequisite of a successful statistical downscaling is that large-scale predictors simulated by the General Circulation Model (GCM) must be realistic. It is assumed here that features smaller than the GCM resolution are important in determining the realism of the large-scale predictors. It is tested whether a three-step method can improve conventional one-step statistical downscaling. The method uses predictors that are upscaled from a dynamical downscaling instead of predictors taken directly from a GCM simulation. The method is applied to downscaling of monthly precipitation in Sweden. The statistical model used is a multiple regression model that uses indices of large-scale atmospheric circulation and 850-hPa specific humidity as predictors. Data from two GCMs (HadCM2 and ECHAM4) and two RCM experiments of the Rossby Centre model (RCA1) driven by the GCMs are used. It is found that upscaled RCA1 predictors capture the seasonal cycle better than those from the GCMs, and hence increase the reliability of the downscaled precipitation. However, there are only slight improvements in the simulation of the seasonal cycle of downscaled precipitation. Due to the cost of the method and the limited improvements in the downscaling results, the three-step method is not justified to replace the one-step method for downscaling of Swedish precipitation.

Conditioning stochastic properties of daily precipitation on indices of atmospheric circulation

AbstractTime series of daily precipitation, at Valentia, Ireland, are examined using conditioned chain‐dependent processes. The conditioning is carried out using two different indices of large‐scale atmospheric circulation. The first conditioning index relates to mean monthly sea level pressure (SLP), conditioned as either above or below the historic monthly mean. The second conditioning index is based on the geostrophic wind direction (GWD), conditioned as being inside or outside the historic storm quadrant for the month. For each conditioning index, there are two conditioned daily models and they differ in the parameters that relate to both occurrence and intensity and therefore to changes in the distribution of monthly total precipitation. The results of conditioning the daily precipitation on SLP are compared with conditioning on GWD. The GWD conditioned model gave similar results to the SLP conditioned model for the wetter months, but performed poorly for the summer season. Combining the two SLP conditioned daily models into an induced model, which is a mixture of the two chain dependent processes, produces a variance for monthly total precipitation that is closer to the observed value than the unconditioned chain‐dependent model. Copyright © 1998 Royal Meteorological Society