Atmospheric circulation, teleconnection patterns

Introduction
Climate is variable in time and space, so detecting a significant trend is a major challenge for researchers. Calculating the trends of climatic elements such as average temperature, maximum, and minimum temperature has been the subject of many studies in recent years. It has been carried out in different regions around the world. Most studies in this field have focused on large-scale temperature trends. However, more research is needed to focus on the change that occurs at the regional level. In this way, the research conducted on the decadal trends of the average temperature in different regions provides impressive results. In order to study how global warming affects life at the regional level, climate change models and assessments often assume that the impact will be uniform. However, temperature does not increase uniformly in space or time.

Materials and Methods
In this research, the analyzed monthly data of ERA-Interim with a resolution of 0.25*0.25 degrees during the time period of 1979-2019 from the ECMWF website (European Center for Weather Forecasting) has been used. According to the area of the Abraqo-Sirjan catchment area and the resolution of the studied data, 338 points of the entire basin were covered and studied. Also, the data of the link indices from the North Atlas and South Atlas regions, which were extracted from the NOA site at the same time as the mentioned period, were used. Pearson's correlation and linear regression tests were used to investigate the relationship between the average temperature of the watershed and the remoteness indices.

Results and Discussion
Examining the average temperature trend of the Abrago-Sirjan basin area showed that except for the months of April, May, August, and December, the other months only have an increasing trend. In April, the northern areas and parts of the west and east of the basin have an increasing trend. Other parts of the basin have no trend. In this month, 37.05% of the area of the basin is covered by the increasing trend zone and 62.94% by the non-trending zone. In May, the northern half of the basin has an increasing trend and covers 48.95% of the area of the basin. The southern half with an area of 29252.85 square kilometers is without trend and covers 51.04% of the area of the basin. In August, only a very small part of the north of the basin showed an increasing trend. This area with an area of 5728.55 square kilometers includes 9.99% of the area of the basin. Other parts of the basin, which includes about 90% of the area of the basin, do not have any trend. In the month of December, the area has been expanding and has covered more parts of the area of the basin. In this month, an increasing trend has been observed in the northern half of the basin, parts of the center, and south of the basin. The area of increasing trend in this month with an area of 43,886.6 km2 has covered 76.57 km2 of the area of the basin. The no-trend area with an area of 13422.44 km2  includes 23.42% of the area of the basin. Correlation between the average temperature of the basin and teleconnection patterns also showed that only the NAO pattern in February showed an inverse correlation at a 95% significance level with the temperature of the basin and other patterns had a direct correlation with the temperature of the basin. In January, TSA and AMO patterns, in February, NAO, TNA, AMO, AMM and NTA patterns; in March TNA, TSA, AMM and NTA patterns; In April, TNA, TSA, AMO patterns; In May, TSA and AMO patterns; In June, the AMO pattern; In July, NTA and TNA patterns; In August, AMO and NTA patterns; In September, AMM and NAO patterns; In November, AMM, AMO and TNA patterns and in December, AMM and TNA patterns have shown correlation with average temperature. In the months of February, March, May, July and September, in addition to the correlation at the significance level of 95%, correlations were also observed at the 99% level, and a major part of the basin has correlations with distant teleconnection patterns.

Conclusion
The results of investigating the average temperature trend of the Abarqo-Sirjan basin showed that the temperature in this basin has only an increasing trend, and during the period of 1979-2019, there was no decreasing trend in the average temperature of this basin. In the months of January, February, March, June, July, September, October, and November, and on an annual scale, all basins have an increasing trend. In the months of April, May, August, and December, apart from the increasing trend zone, the no-trend zone is also observed at the basin level. Among the studied patterns, the AMO pattern has shown more correlation with the average temperature of the basin than other patterns. After that, TNA, AMM, NTA, and TSA patterns have the highest correlation. In the cold months of the year, the lowest correlation between the distance and average temperature of the basin was observed, and in the warm months of the year, a larger area of the basin showed a correlation.

We study the effect of a thermal forcing confined to the midlatitudes of one hemisphere on the eddy-driven jet in the opposite hemisphere. We demonstrate the existence of an "interhemispheric teleconnection," whereby warming (cooling) the Northern Hemisphere causes both the intertropical convergence zone (ITCZ) and the Southern Hemispheric midlatitude jet to shift northward (southward). The interhemispheric teleconnection is effected by a change in the asymmetry of the Hadley cells: as the ITCZ shifts away from the Equator, the cross-equatorial Hadley cell intensifies, fluxing more momentum toward the subtropics and sustaining a stronger subtropical jet. Changes in subtropical jet strength, in turn, alter the propagation of extratropical waves into the tropics, affecting eddy momentum fluxes and the eddy-driven westerlies. The relevance of this mechanism is demonstrated in the context of future climate change simulations, where shifts of the ITCZ are significantly related to shifts of the Southern Hemispheric eddy-driven jet in austral winter. The possible relevance of the proposed mechanism to paleoclimates is discussed, particularly with regard to theories of ice age terminations.

The Madden-Julian Oscillation is one of the large-scale climate change patterns in the maritime tropics, with subseasonal time periods of 30 to 60 days affecting tropical and subtropical regions. This phenomenon can cause changes in various quantities of the atmosphere and ocean, such as pressure, sea surface temperature, and the rate of evaporation from the ocean surface in tropical regions. In this research, the effects of Madden-Julian fluctuation on the weather elements of Iran have been investigated with the aim of knowing the effects of different phases in order to improve the quality of forecasts and benefits in territorial planning. At first, the daily rainfall data of 1980-2020 were received from the National Meteorological Organization and quality controlled. Using the Wheeler and Hendon method, the two main components RMM1 and RMM2 were analyzed, based on which the amplitude of the above two components is considered as the main indicator of the intensity and weakness of this fluctuation. This index is based on the experimental orthogonal functions of the meteorological fields, including the average wind levels of 850 and 200 hectopascals and outgoing long wave radiation (OLR) between the latitudes of 20 degrees south and 20 degrees north. The clustering of the 7-day sequence with a component above 1 was used as the basis for clustering all eight phases, and by calculating the abnormality of each phase compared to its long term in the DJF time frame, the zoning of each phase was produced separately. In the end, phases 1, 2, 7, 8 were concluded as effective phases in Iran's rainfall and phases 3, 4, 5, 6 as suppressive phases of Iran's rainfall.

Rapid Arctic warming is hypothesized to favor an increased persistence of regional weather patterns in the Northern Hemisphere (Francis & Vavrus, 2012). Persistent conditions can lead to drought, heat waves, prolonged cold spells, and storminess that can cost millions of dollars in damage and disrupt societal and ecosystem norms. This study defines a new metric called long‐duration events (LDEs)—conditions that endure at least four consecutive days—and takes two independent approaches to assessing seasonal changes in weather‐pattern persistence over North America. One applies precipitation measurements at weather stations across the United States; the other is based on a cluster analysis of large‐scale, upper‐level atmospheric patterns. Both methods indicate an overall increase in LDEs. We also find that large‐scale patterns consistent with a warm Arctic exhibit an increased frequency of LDEs, suggesting that further Arctic warming may favor persistent weather patterns that can lead...

The predictability of the Magdalena River seasonal streamflow anomalies is evaluated using previous Sea Surface Temperature (SST), Precipitation (Pt) and Temperature over land (Tm) seasonal anomalies. Through a moving correlation analysis of 30 years, several regions that show stable significant teleconnections between the seasonal streamflow and SST, Pt and Tm from previous seasons have been identified during the period 1936-2009. For lags from one to four 3-month seasons (i.e. up to one year) for the SST and one to two seasons (i.e. up to six months) for Pt and Tm, the Magdalena River seasonal streamflow presents significant and stable correlations with the tropical Pacific SST (El Niño region), with Pt in South America and with Tm over the north of South America, mainly at lags of one and two seasons. The first PCs resulting from the significant and stable regions of the SST, Pt, and Tm fields are used in a forecast scheme to predict seasonal streamflow anomalies. The prediction based on this scheme shows an acceptable prediction skill and represents a relative improvement compared with the predictability of teleconnection indices associated with El Niño, which are traditionally used to predict streamflow in the country. This improvement is particularly more noticeable when lag between streamflow and predictors increases.

Climate variability can be identified based on two climate parameters: Outgoing Longwave Radiation (OLR) and Precipitable Water (PW). South of Indonesia (2-10 o S, 90-15 o E) is a rainfall monsoon region with relatively homogeneous characteristics in seasonal variations. However, the region has some certain sensitivities in responding variability from intraseasonal to interannual. Using the method of Empirical Mode Decomposition (EMD), S-Transform and Wavelet for 30 years monthly data of OLR and PW (1980-2011), it was found that both of data indicate signal strengthening after 2010 which is related to Tropical Multidecadal Mode. Regional response from Intraseasonal to interannual variations confirm that both parameters are sensitive to 1-3 monthly (Intraseasonal Variation) related to MJO, 6 month and 1 year related to monsoon, the 2-7 year variability associated with El Niño Southern Oscillation (ENSO) on short term and medium scale period, whereas 10 yearly due to ENSO in longterm scale period and probably represent the phenomenon of the solar cycle. However it may be suggested that the 15 and 30 year variability would probably corresponded with ENSO and the Pacific Decadal Oscillation (PDO).

This paper presents application of climate information to the prediction of seasonal reservoir inflow for Kainji hydropower generation dam in Nigeria. The direct linkage between Oct-Nov-Dec (OND) seasonal stream flows and Sea Surface Temperature (SST) of the preceding Jul-Aug-Sept (JAS) season extracted from Atlantic and ENSO index (NINO3) in the NOAA's climate diagnostic center's interactive plotting and analysis tool were identified by performing diagnostic analysis using lag-3 correlation. It was observed that the correlation between reservoir inflow and Atlantic Ocean SST is -0.40, and for ENSO index (NINO3) about -0.60. Negative correlation implies that positive increase in SST anomalies lead to decrease in stream flow. Once the linkages has been established, the predictor variable, (SST anomalies) were selected from the KAPLAN data bank for different regions of significant correlation, which include US coast, North Atlantic, South Atlantic and ENSO index (NINO3) and th...

Rapid Arctic warming is hypothesized to favor an increased persistence of regional weather patterns in the Northern Hemisphere (Francis & Vavrus, 2012). Persistent conditions can lead to drought, heat waves, prolonged cold spells, and storminess that can cost millions of dollars in damage and disrupt societal and ecosystem norms. This study defines a new metric called long‐duration events (LDEs)—conditions that endure at least four consecutive days—and takes two independent approaches to assessing seasonal changes in weather‐pattern persistence over North America. One applies precipitation measurements at weather stations across the United States; the other is based on a cluster analysis of large‐scale, upper‐level atmospheric patterns. Both methods indicate an overall increase in LDEs. We also find that large‐scale patterns consistent with a warm Arctic exhibit an increased frequency of LDEs, suggesting that further Arctic warming may favor persistent weather patterns that can lead...

This study has investigated the spatiotemporal structure and changes in Lake Michigan snowfall for the period 1950–2013. With data quality caveats acknowledged, a larger envelope of stations was included than in previous studies to explore the data using time series analysis, principal component analysis, and geographic information systems. Results indicate warming in recent decades, a near-dearth of serial correlation, midwinter dependence on teleconnection patterns, strong sensitivity of snowfall to temperature, peak snowfall variability and dependence on temperature within the lake-effect belt, an increasing fraction of seasonal snowfall occurring from December to February, and temporal behavior consistent with the previously reported trend reversal in snowfall.

Özet Türkiye'de boydan boya seçilen 32 istasyondan alınan aylık minimum ortalama sıcaklık değerleri ile arktik salınım indis değerleri arasında anlamlı negatif bir korelasyon olduğu gözlemlenmektedir. Bununla birlikte Türkiye'nin batısına gidildikçe istasyonların arktik salınıma verdiği tepki giderek ilginç bir şekilde değişmekte, korelasyon anlamlık dereceleri daha zayıf hale gelmektedir. Korelasyon değerleri üzerinde karasal, denizel faktörlerin açık etkilerinin olduğunu görmekteyiz. Bu etki sıcaklık değerleri ile atmosferik salınımlar arasında daha net bir şekilde görülmektedir. Arktik salınım özellikle karasal iklimin egemen olduğu yerlerde bulunan istasyonların sıcaklık değerleri üzerinde etkilidir. Öte yandan denizel iklimin egemen olduğu alanlarda yer alan istasyonlarda bu etki ya çok zayıf ya da çok anlamsız bir korelasyon şeklindedir. Genel olarak aylık minimum ortalama sıcaklık değerleri ile arktik salınım indis değerleri arasında negatif bir korelasyon mevcuttur. Başka bir ifade ile arktik salınım indis değerleri düştükçe Türkiye'de aylık minimum ortalama sıcaklıklar artmaktadır. Arktik salınımın Türkiye'deki istasyonların aylık minimum ortalama sıcaklık değerleri üzerindeki etkileri barizdir. Eğilimler Aralık, Ocak, Şubat ve Mart aylarında anlamlıdır.

Results from diagnostic analyses to understand the seasonal evolution of the large-scale climatic state responsible for the development and melt of the winter snowpack, and spring-early summer precipitation in the Churchill Falls region on the Québec-Labrador Peninsula, Canada, are presented in the context of the development of an empirical model for seasonal to annual streamflow forecasting, with a special emphasis on the May-July spring freshet. Teleconnection indices and gridded global measures of atmospheric circulation inferred from the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis are used as climatic indicators. Composite and correlation analyses are applied to the climatic indicators conditioned on the spring streamflow for identification of potential predictors. Meridional and zonal atmospheric fluxes over the Atlantic and the Pacific Oceans emanating from regionally persistent sea surface temperature/sea level pressure modes are identified as potential carriers of information. We speculate on the ocean-atmosphere and regional hydrologic mechanisms that may be involved in lending multiseasonal predictability to streamflows in the region.

ENSO is one of the primary modes of climate variability in the tropics. It can be predicted with reasonable skill with time leads of at least six months and can form the foundation for mitigation of the impacts of frequents floods, droughts and water management problems. This study attempts to establish a relationship between ENSO and stream flow in the Athi river basin in Kenya and develop a forecasting model for seasonal stream flow in the basin. Stream flow data from the Athi river basin was subjected to homogeneity analysis using the runs and the mass curve methods. The Principal component analysis was used to study the spatial variability of stream flow in the Athi river basin while simple correlation method was used to investigate the link between streamflow and ENSO indicators. The long range seasonal forecasts models were developed using step-wise regression method and the non-parametric seasonal forecasting model (NSFM). The results for spatial characteristics of seasonal streamflow in the Athi river basin showed a strong influence of the north-south oscillation of the ITeZ, the land and sea meso scale circulation system, orography and land use effects on seasonal variability of stream flow. The results for the teleconnection showed a significant correlation between streamflow and ENSO indicators at various lags. The results for the regression models indicated that SON streamflow could be predicted 3 months earlier using May-June SOL The results for NSFM streamflow showed that the February-March streamflow could predict SON streamflow at lag 6 with good prediction skills of E = 0.4 and LEPS = 40% at calibration and E = 0.3 LEPS = 33% at verification stage. The results show that it is possible to use ENSO indicators to forecast stream flow hence making it possible for the authority to give early warning system on the use water resources in the basin.

Teleconnection patterns are one of the key features to understanding highfrequency natural climate variability. The North Sea-Caspian Pattern (NCP) was identified as a middle tropospheric dipole and its hydroclimatological implications have been substantially restricted to the Eastern Mediterranean region.

In recent years, the damages resulting from abnormal hydrometeorological climate have substantially increased over the world due to the climate variability and change. Especially, the flood damage has been severely occurred during the flood season almost every year in Korea. For an example, we had the localized heavy rainfalls for 54 days in flood season of 2020 and had huge property damage and loss of life. Therefore, the study needs to be conducted to improve the predictive power of seasonal time-scale forecasts spanning one to several months for the damage reduction and prevention. In this regard, this study aims to provide a priori predictions (several months ahead) of the climate variable at target sites with a statistical method based on teleconnection with global climatic conditions. Herein, the paradigm of the temperature and precipitation prediction in the Geum river basin in Korea is presented. The purposes of the study are also (1) to analyse the characteristics of summer...

This paper presents application of climate information to the prediction of seasonal reservoir inflow for Kainji hydropower generation dam in Nigeria. The direct linkage between Oct-Nov-Dec (OND) seasonal stream flows and Sea Surface Temperature (SST) of the preceding Jul-Aug-Sept (JAS) season extracted from Atlantic and ENSO index (NINO3) in the NOAA's climate diagnostic center's interactive plotting and analysis tool were identified by performing diagnostic analysis using lag-3 correlation. It was observed that the correlation between reservoir inflow and Atlantic Ocean SST is -0.40, and for ENSO index (NINO3) about -0.60. Negative correlation implies that positive increase in SST anomalies lead to decrease in stream flow. Once the linkages has been established, the predictor variable, (SST anomalies) were selected from the KAPLAN data bank for different regions of significant correlation, which include US coast, North Atlantic, South Atlantic and ENSO index (NINO3) and th...

Testing the significance of observed trends in hydro-meteorological time series has received a great attention recently, especially in connection with climate change. The changing pattern of rainfall deserves urgent and systematic attention for planning, development, utilisation and management of water resources. The daily data on variable were converted to monthly and then computed to seasonal and annual series. Annual rainfall (mm/yr) was calculated as the sum of monthly values. The missing values in the data were computed by using average method. The records of rainfall were subjected to trend analysis by using both non-parametric (Mann-Kendall test) and parametric (linear regression analysis) procedures. For better understanding of the observed trends, data were computed into standardised precipitation indices (SPI). These standardised data series were plotted against time and the linear trends observed were represented graphically. Trend analysis results of rainfall show that o...

This paper reviews recent advances regarding land–atmosphere–ocean coupling associated with the Tibetan Plateau (TP) and its climatic impacts. Thermal forcing over the TP interacts strongly with that over the Iranian Plateau, forming a coupled heating system that elevates the tropopause, generates a monsoonal meridional circulation over South Asia and creates conditions of large-scale ascent favorable for Asian summer monsoon development. TP heating leads to intensification and westward extension (northward movement) of the South Asian High (Atlantic Intertropical Convergence Zone), and exerts strong impacts on upstream climate variations from North Atlantic to West Asia. It also affects oceanic circulation and buoyancy fields via atmospheric stationary wave trains and air–sea interaction processes, contributing to formation of the Atlantic Meridional Overturning Circulation. The TP thermal state and atmospheric–oceanic conditions are highly interactive and Asian summer monsoon vari...

During the second half of August 2022, a dust intrusion event occurred when dust that originated in the dry regions of the Kalmyk steppe (located in Russia, northeast of the Black Sea, north of Georgia, and northwest of the Caspian Sea) and the Precaspian plain was transported over the eastern region of Romania. The arid soil found in these areas can be attributed to an extended period of intense drought, with notable instances occurring in 2002, 2003, 2015, and 2018. This situation was further intensified by heatwaves experienced in May and June of 2022. The dust event was captured in MODIS images. In addition, smoke trains originating from fires in the north of the Azov were de-tected, but these did not reach Romania. Optical parameters from AERONET were used to confirm the dust event. To determine the trajectory of the particles, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used in this paper. The ensemble median model was used to highlight the presence and concentration of dust in the eastern part of Romania. Aerosols were detected between 0 and 4 km, according to radar and ceilometer data from the REXDAN cloud remote sensing facility in Galați, Romania. This dust intrusion event was the result of the dominant easterly circulation caused by the extension of the East European High to the northeast of the continent, which transported the dust towards the eastern part of Romania for more than 2 days. Moreover, the torrential rains between 22 and 24 August  did not clear the atmosphere of dust, since the intense easterly circulation kept carrying the dust into the Moldavian area.

There are about 6,800 lakes in the Polish Lowlands. They are a potential place for rest and recreation not only for the local population, but also for those coming from other regions of Poland and foreign guests. The work was based on the analysis of water temperature data in lakes in the years 1961–2020. The highest surface water temperatures in lakes occurred most often at the turn of the last decade of July and the fi rst decade of August, reaching values above 2 °C in most lakes. In the daily cycle, the highest water temperatures in the surface water layer (up to 1.5 m deep) were recorded mostly between 14:00 and 17:00 (13:00–16:00 GMT). The beginning of the bathing season on lakes in Poland usually falls between May 20 and 25, while the end is in the second half of September, reaching an average of about 69 days, characterized by a positive trend in its duration. According to the Chief Sanitary Inspectorate in Poland, in 2020 there were 602 active bathing areas, most of which w...

The demand for freshwater is increasingly increasing, while the limited water resources are subject to over-harvesting, pollution, and climate change, which require the improvement of water resource management to distribute it equitably and achieve It highlights the goals of sustainable development. A low-cost option to support better water management strategies is to develop models capable of predicting available water amounts, especially amounts related to precipitation and river flow. Climatic diversity and climate changes are basic assumptions for hydro climatological predictions. One of the remarkable aspects of this issue is the correlation between large-scale atmospheric-oceanic phenomena or long-term patterns with hydrological processes on a local scale, and these patterns can also affect the inflow to the dams. This study uses three machine learning models, an artificial neural network, a Bayesian neural network, and an adaptive neuro-fuzzy inference system to predict the inflow to the dams and evaluate their efficiency. For this purpose, 12 scenarios consisting of rainfall variables, inflow to the dam, and nine climatic indicators with a delay of up to six-time steps were designed to investigate the effect of using long-term models as predictive variables of the flow one month later in Amirkabir Dam. to be placed The analysis of the results of this research showed that the use of the Nino3.4 index with one-time step delay as well as the PDO index with two-time step delays can increase the accuracy of the model compared to the scenarios in which only station variables are used. to be According to the results, the Nino 3.4 index was found to be the most effective index on the inflow to Amirkabir Dam, and the scenario in which the mentioned index along with the rainfall and flow data of one and two months before was used as input, in all three The model recorded the highest accuracy. Also, the performance of the ANFIS model for the mentioned scenario (scenario 9), with RMSE and R2 values, equal to 5.69 and 0.79 cubic meters per second, respectively, was better than the ANN and BNN models, so the value of the R2 index for the best scenario consisting of station variables (scenario 5), it increased by 0.15 and the value of RMSE index decreased by 0.78 cubic meters.

The Mississippi River basin drains nearly one-half of the contiguous United States, and its rivers serve as economic corridors that facilitate trade and transportation. Flooding remains a perennial hazard on the major tributaries of the Mississippi River basin, and reducing the economic and humanitarian consequences of these events depends on improving their seasonal predictability. Here, we use climate reanalysis and river gauge data to document the evolution of floods on the Missouri and Ohio Rivers—the two largest tributaries of the Mississippi River—and how they are influenced by major modes of climate variability centered in the Pacific and Atlantic Oceans. We show that the largest floods on these tributaries are preceded by the advection and convergence of moisture from the Gulf of Mexico following distinct atmospheric mechanisms, where Missouri River floods are associated with heavy spring and summer precipitation events delivered by the Great Plains low-level jet, whereas Oh...

The Tibetan Plateau (TP), as a whole, has undergone a moistening process since the late 1990s. However, the southern Tibetan Plateau (STP) is an exception, where summer monsoon precipitation amount has decreased, and lakes have shrunk. The cause for the precipitation decrease is not clear yet. Here we show that the monsoon (June to September) mean precipitation changes in the STP from 1979 to 2018 features a decadal variation component with a peak of around ten years that is superposed on an upward ‘trend’ from 1979 to 1998 and a downward ‘trend’ afterward. We find that the decadal variation of the STP precipitation is associated with a large-scale dipolar sea surface temperature (SST) pattern between the equatorial central Pacific and the Indo-Pacific warm pool. A wet STP corresponds to negative SST anomaly in the equatorial central Pacific and positive SST anomaly in the Indo-Pacific warm pool. This equatorial SST gradient in the western Pacific generates pronounced easterly anomalies and a dipolar rainfall anomaly (i.e., a positive rainfall anomaly over the Maritime Continent and a negative anomaly in the equatorial western and central Pacific). Due to less precipitation over the equatorial western Pacific, the suppressed heat source appears to excite an anomalous anticyclonic band along 15-20°N extending from the Philippine Sea to the Bay of Bengal by emanating westward propagating descending transient Rossby waves. The low-level anticyclonic circulation over the Bay of Bengal further enhances northward moisture transport toward the STP and promote upward motion in the STP through changing local meridional circulation. Besides, the linearized atmospheric general circulation model experiments demonstrate that the dipole heating source can generate a high-pressure zone under the control of anticyclone over the western Pacific, which can extend westward to the Indian monsoon region.

Pakistan summer monsoon rainfall consists of a large portion of the local annual total rainfall, and in the recent monsoon seasons, prolonged periods of anomalous rainfall and excessive flooding have appeared in Pakistan. A full understanding of the monsoon rainfall variability is important for the sustainable development of the country. Based on multiple data analyses and the weather research and forecasting model, the potential impact of Tibetan Plateau (TP) heating on the interannual variability of Pakistan monsoon rainfall is investigated. It is observed that a significant negative relationship exists between the thermal forcing over the southeastern TP and Pakistan monsoon rainfall in July-August. Both the data analyses and model sensitivity experiments identify that the TP heating drives a Rossby wave response in the upper atmosphere characterized with an anticyclonic anomaly over the southern TP but a cyclonic anomaly to the north. This dipole pattern of anomalous circulation induces an evident upper-level convergence over Pakistan, corresponding with remarkable vertical sinking motion. Meanwhile, in the lower troposphere, the TP heating causes anomalous westerly wind along the Himalayas over the northern India continent. Such westerly anomaly further induces less water vapor transport into Pakistan from the Bay of Bengal. Therefore, both the dynamic and thermodynamic processes regulated by positive TP heating are not beneficial for the occurrence of monsoon rainfall in Pakistan. This study proposes a new potential mechanism in which TP heating acts as a driver of Pakistan monsoon rainfall variability on interannual time scales.

Drought forecasting can aid in developing mitigation strategies and minimizing economic losses. Drought may be forecast using a drought index, which is an indicator of drought. The agricultural reference index for drought (ARID) was used as a tool to investigate the possibility of using climate indices (CIs) as predictors to improve the current level of forecasting, which is El Niño–Southern Oscillation (ENSO) based. The performances of models that are based on linear regression (LR), artificial neural networks (ANN), adaptive neuron-fuzzy inference systems (ANFIS), and autoregressive moving averages (ARMA) models were compared with that of the ENSO approach. Monthly values of ARID spanning 56 yr were computed for five locations in the southeastern United States, and monthly values of the CIs having significant connections with weather in this region were obtained. For the ENSO approach, the ARID values were separated into three ENSO phases and averaged by phase. For the ARMA models...

The Mississippi River basin drains nearly one-half of the contiguous United States, and its rivers serve as economic corridors that facilitate trade and transportation. Flooding remains a perennial hazard on the major tributaries of the Mississippi River basin, and reducing the economic and humanitarian consequences of these events depends on improving their seasonal predictability. Here, we use climate reanalysis and river gauge data to document the evolution of floods on the Missouri and Ohio Rivers—the two largest tributaries of the Mississippi River—and how they are influenced by major modes of climate variability centered in the Pacific and Atlantic Oceans. We show that the largest floods on these tributaries are preceded by the advection and convergence of moisture from the Gulf of Mexico following distinct atmospheric mechanisms, where Missouri River floods are associated with heavy spring and summer precipitation events delivered by the Great Plains low-level jet, whereas Oh...

The study forecasts the streamflow at a regional scale within SSJ river basin with largescale climate variables. The proposed approach eliminates the bias resulting from predefined indices at regional scale. The study was performed for eight unimpaired streamflow stations from 1962-2016. First, the Singular Valued Decomposition (SVD) teleconnections of the streamflow corresponding to 500 mbar geopotential height, sea surface temperature, 500 mbar specific humidity (SHUM 500), and 500 mbar U-wind (U 500) were obtained. Second, the skillful SVD teleconnections were screened non-parametrically. Finally, the screened teleconnections were used as the streamflow predictors in the non-linear regression models (K-nearest neighbor regression and data-driven support vector machine). New hydrological insights: The SVD results identified new spatial regions that have not been included in existing predefined indices. The nonparametric model indicated the teleconnections of SHUM 500 and U 500 being better streamflow predictors compared to other climate variables. The regression models were capable to apprehend most of the sustained low flows, proving the model to be effective for drought-affected regions. It was also observed that the proposed approach showed better forecasting skills with preprocessed large scale climate variables rather than using the predefined indices. The proposed study is simple, yet robust in providing qualitative streamflow forecasts that may assist water managers in making policy-related decisions when planning and managing watersheds.

The study evaluated the relationship between two climate variability indicatorsseasurface temperature (SST) and 500-mbar geopotential height (HGT/Z500)and the monsoonal precipitation pattern of Pakistan. Data from 30 precipitation gauges were obtained and were analyzed over a period of 35 years from 1980 to 2014. Singular-valued decomposition (SVD) technique was used to determine the association of previous year's SST and HGT with the current year's monsoonal precipitation. The results indicated that the association of SST and HGT with precipitation varied depending on the lead-times selected. Multiple regions of the North Indian Ocean were identified that showed significant association in affecting Pakistan's precipitation. The long term trend and abrupt shift patterns of precipitation were also evaluated across the selected gauges to determine the generic change patterns. The findings of the study can be useful predictors of forecasting models for water management in Pakistan.

In this study, an attempt has been made to work out water balance, determine rate of sedimentation and physico-chemical analysis of the lake water. The water balance is carried out using the mass balance equation to account for various input and output components. Sedimentation rates and pattern are estimated using 137 Cs and 210 Pb radiometric dating techniques. The physico-chemical analysis of the lake water is done by collecting samples from twelve locations of the lake at three different depths. The major inflow to the lake is catchment runoff, which accounts for nearly 56% of the total annual inflow and about 98% inflow takes place during monsoon period. The major outflow from the lake is weir overflow, which occurs in monsoon season only and accounts for about 85% of the total annual outflow. The estimated mean sedimentation rate in the lake is 0.58±0.028 cm/year. The estimated useful life of the lake based on post-1964 (appearance of the major peak of 137 Cs due to weapon fallout record pattern) average sedimentation rate is around 467± 23 years. The lake has attained the hyper-eutrophic state due to high nitrogen and phosphorous contents in the lake water. Based on the trophic state index (TSI), the lake has become unsuitable for drinking, bathing and even for fish culture.

Large-scale climate can provide predictive information for streamflow forecasts in many parts of the world. However, the optimal selection of predictors can be problematic when focusing on a localized region. This work evaluated multiple gridded climate datasets in order to determine optimal predictors of seasonal streamflow in West-Central Florida. Using persistence in streamflow, existing indices of climate, and sea surface temperature (SST) expansion coefficient time-series from singular value decomposition (SVD) analysis, this work developed probability of exceedance streamflow forecasts for multiple stations, seasons, and lead-times. Forecasts were found to be generally skillful between the September-November and April-June seasons with this range narrowing as lead time increased and skill was mainly related to the impact of the El Niño-Southern Oscillation (ENSO) on the region. Using multiple indices of ENSO that were determined by correlation and composite analyses to track its evolution from the west Pacific at long lead-times to the east Pacific at short lead-times was not found to appreciably improve forecasts over using the Niño 3.4 index alone. Using SST expansion coefficient time-series from SVD analysis was found to capture the evolution of ENSO from west to east and to provide skillful forecasts of streamflow at earlier leads (up to 7 months in advance) compared to that found by pre-defined indices, indicating the importance of predictor selection in achieving optimal forecast skill.

Shallow, lagoonal coastal lakes of the Southern Baltic are exceptionally susceptible to atmospheric factors. This work examines the influence of winter air temperatures in Ustka on ice parameters (dates of first ice occurrence and last ice disappearance, ice season duration, number of days with ice, and maximum ice thickness) on Southern Baltic coastal lakes (Jamno, Bukowo, Gardno, Łebsko), and trends displayed by changes in these parameters over the period spanning 1960/61-2019/20. The research data was retrieved from the archives of Institute of Meteorology and Water Management – National Research Institute. As a first step of the analysis, we investigated the statistical relationships in spatial and temporal variations in winter air temperature and coastal lake ice parameters. Correlation and regression method was employed to determine the influence of air temperature on coastal lake ice conditions. Correlation and determination coefficients were calculated, and linear regression...

Interannual variations of catchment streamflow represent an integrated response to anomalies in regional moisture transport and atmospheric circulations, ultimately linked to large-scale climate oscillations. This study investigates the relationship between Taiwan's long-term summertime (July to September, JAS) streamflow and manifold teleconnection patterns. Lagged correlation analysis is conducted to calculate how JAS streamflow data derived at 28 upstream and 13 downstream gauges in Taiwan correlate with 14 teleconnection indices in the concurrent or preceding seasons. Out of the many indices, the West-Pacific and Pacific-Japan (PJ) patterns, both of which play a critical role in determining cyclonic activity in the western North Pacific basin, exhibit the highest concurrent correlations (most significant <i>r</i> = 0.48) with the JAS flows in Taiwan. At a one-month lead time, on the other hand, the Quasi-Biennial Oscillation significantly correlate with the JAS f...

Interannual variations in catchment streamflow represent an integrated response to anomalies in regional moisture transport and atmospheric circulations and are ultimately linked to large-scale climate oscillations. This study conducts correlation analysis to calculate how summertime (July-September, JAS) streamflow data derived at 28 upstream and 13 downstream gauges in Taiwan correlate with 14 teleconnection indices in the current or preceding seasons. We find that the western Pacific (WP) and Pacific-Japan (PJ) patterns, both of which play a critical role in determining cyclonic activity in the western North Pacific basin, exhibit the highest concurrent correlations (most significant r = 0.50) with the JAS flows in Taiwan. Alternatively, the Quasi-Biennial Oscillation (QBO) averaged over the period from the previous October to June of the current year is significantly correlated with the JAS flows (most significant r = −0.66), indicating some forecasting utility. By further examining the correlation results using a 20-year moving window, peculiar temporal variations and possible climate regime shifts (CRSs) can be revealed. A CRS test is employed to identify suspicious and abrupt changes in the correlation. The late 1970s and 1990s are identified as two significant change points. During the intermediate period, Taiwan's streamflow and the PJ index exhibit a marked inphase relationship (r > 0.8). It is verified that the two shifts are in concordance with the alteration of large-scale circulations in the Pacific basin by investigating the changes in pattern correlation and composite maps before and after the change point. Our results suggest that empirical forecasting techniques should take into account the effect of CRSs on predictor screening.

El Niño/Southern Oscillation (ENSO) events are classically associated with a significant increase in the length of day (LOD), with positive mountain torques arising from an east-west pressure dipole in the Pacific driving a rise of atmospheric angular momentum (AAM) and consequent slowing of the Earth's rotation. The large 1982-83 event produced a lengthening of the day of about 0.9 ms, while a major ENSO event during the 2015-16 winter season produced an LOD excursion reaching 0.81 ms in January 2016. By evaluating the anomaly in mountain and friction torques, we found that: (i) as a mixed Eastern/Central Pacific event, the 2015-16 mountain torque was smaller than for the 1982-83 and 1997-98 events which were pure Eastern Pacific events, and (ii) the smaller mountain torque was compensated by positive friction torques arising from an enhanced Hadley-type circulation in the Eastern Pacific, leading to similar AAM/LOD signatures for all three extreme ENSO events. The 2015-16 event thus contradicts the dominant paradigm that mountain torques cause the Earth rotation response for extreme El Niño events. 1 Introduction Earth rotation fluctuates with time, as a response to the interaction of the solid Earth with celestial bodies, the liquid core, and the fluid layers of the climate system. This interaction results in changes of the orientation of the Earth rotation vector in space, of the orientation of the Earth around its rotation axis, and of the Earth rotation angular velocity associated with changes in the length of the day (LOD). Variations of the LOD can reach a few milliseconds on the timescale of a few tens of years, due to core-mantle interaction (Holme and de Viron, 2013, and references therein), and a few tenths of a millisecond on the timescale of some days to several years, due mostly to solid-Earth/atmosphere interaction (Hide and Dickey, 1991), though the solid-Earth/ocean interaction does play a small role (

Extratropical atmosphere–ocean variability over the Northern Hemisphere of the Community Climate System Model version 3 (CCSM3) is examined and compared to observations. Results are presented for an extended control integration with a horizontal resolution of T85 (1.4°) for the atmosphere and land and ∼1° for the ocean and sea ice. Several atmospheric phenomena are investigated including storms, clouds, and patterns of variability, and their relationship to both tropical and extratropical SST anomalies. The mean storm track, the leading modes of storm track variability, and the relationship of the latter to tropical and midlatitude sea surface temperature (SST) anomalies are fairly well simulated in CCSM3. The positive correlations between extratropical SST and low-cloud anomalies in summer are reproduced by the model, but there are clear biases in the relationship between clouds and the near-surface meridional wind. The model accurately represents the circulation anomalies associat...

BackgroundThe impact of weather on morbidity from stroke has been analysed in previous studies. As the risk of stroke was mostly associated with changing weather, the changes in the daily stroke occurrence may be associated with changes in atmospheric circulation. The aim of our study was to detect and evaluate the association between daily numbers of ischaemic strokes (ISs) and haemorrhagic strokes (HSs) and the teleconnection pattern.MethodsThe study was performed in Kaunas, Lithuania, from 2000 to 2010. The daily numbers of ISs, subarachnoid haemorrhages (SAHs), and intracerebral haemorrhages (ICHs) were obtained from the Kaunas Stroke Register. We evaluated the association between these types of stroke and the teleconnection pattern by applying Poisson regression and adjusting for the linear trend, month, and other weather variables.ResultsDuring the study period, we analysed 4038 cases (2226 men and 1812 women) of stroke. Of these, 3245 (80.4%) cases were ISs, 533 (13.2%) cases...

A systematic temporal and spatial analysis is being conducted at the U.S. EPA on historical precipitation and stream flow in the Lower Mississippi River basin (LMRB) and their relationships with Atlantic hurricanes and flooding events. The objectives are to decipher the periodicity and long-term trends exhibited in the hydroclimatic regime, and to determine their implications on the security of community water supplies in the region and the Gulf Coast, the parts of the continental U.S. prone to the negative impacts of extreme weather events under the current and future climate conditions. Statistical modeling using wavelet functions shows periodicity of continental precipitation and hurricanes with characteristic changes of trends around 1890-1900, 1940-1960, and the 1990s. These long-term decadal and multi-decadal changes were identified in a spatial modeling and wavelet frequency analysis of the 24-hour daily precipitation data obtained from the National Climatic Data Center. Long-term variations are also detected in hurricane and flooding events. Based on these findings, one can incorporate the hydroclimatic periodicity and long-term variations into the emergency water supply management and system designs. Measures such as water intake protection, using decentralized water supply, and planning emergency management are potential options in natural disaster preparedness. The results of the first phase investigation are discussed.

In this study, an attempt has been made to work out water balance, determine rate of sedimentation and physico-chemical analysis of the lake water. The water balance is carried out using the mass balance equation to account for various input and output components. Sedimentation rates and pattern are estimated using 137 Cs and 210 Pb radiometric dating techniques. The physico-chemical analysis of the lake water is done by collecting samples from twelve locations of the lake at three different depths. The major inflow to the lake is catchment runoff, which accounts for nearly 56% of the total annual inflow and about 98% inflow takes place during monsoon period. The major outflow from the lake is weir overflow, which occurs in monsoon season only and accounts for about 85% of the total annual outflow. The estimated mean sedimentation rate in the lake is 0.58±0.028 cm/year. The estimated useful life of the lake based on post-1964 (appearance of the major peak of 137 Cs due to weapon fallout record pattern) average sedimentation rate is around 467± 23 years. The lake has attained the hyper-eutrophic state due to high nitrogen and phosphorous contents in the lake water. Based on the trophic state index (TSI), the lake has become unsuitable for drinking, bathing and even for fish culture.

The Lower Sebou Basin, placed in a Mediterranean climate, has the particularity of being exposed to the influence of disturbances from the Atlantic Ocean, making periods of drought and climatic phenomena variable in space and time. Applying the world's most recognized drought indices, shows that the duration, frequency and severity of droughts have increased since the start of the 21st century. These results revealed and placed in the even wider regional climatic context, including the two dominant atmospheric oscillations such as the North Atlantic Oscillation (NAO) and the Mediterranean Oscillation (MO), suggest that the significant drought trends determined are correlated with the relative facts of the two oscillations.

This paper extends the work of Bracco and Pedlosky (2003) investigating the eddy formation mechanism in the eastern Labrador Sea by including a more realistic depiction of the boundary current. The quasigeostrophic model consists of a meridional, coastally-trapped current with three vertical layers. The current configuration and topographic domain are chosen to match as closely as possible the observations of the boundary current and the varying topographic slope along the West Greenland coast. The role played by the bottom-intensified component of the boundary current on the formation of the Labrador Sea “Irminger Rings” is explored. Consistent with the earlier study, a short, localized bottom-trapped wave is responsible for most of the perturbation energy growth. However, in order for the instability to occur in the three-layer model the deepest component of the boundary current must be sufficiently strong, highlighting the importance of the near-bottom flow. The model is able to ...

The study evaluated the relationship between two climate variability indicatorsseasurface temperature (SST) and 500-mbar geopotential height (HGT/Z500)and the monsoonal precipitation pattern of Pakistan. Data from 30 precipitation gauges were obtained and were analyzed over a period of 35 years from 1980 to 2014. Singular-valued decomposition (SVD) technique was used to determine the association of previous year's SST and HGT with the current year's monsoonal precipitation. The results indicated that the association of SST and HGT with precipitation varied depending on the lead-times selected. Multiple regions of the North Indian Ocean were identified that showed significant association in affecting Pakistan's precipitation. The long term trend and abrupt shift patterns of precipitation were also evaluated across the selected gauges to determine the generic change patterns. The findings of the study can be useful predictors of forecasting models for water management in Pakistan.

Large-scale climate can provide predictive information for streamflow forecasts in many parts of the world. However, the optimal selection of predictors can be problematic when focusing on a localized region. This work evaluated multiple gridded climate datasets in order to determine optimal predictors of seasonal streamflow in West-Central Florida. Using persistence in streamflow, existing indices of climate, and sea surface temperature (SST) expansion coefficient time-series from singular value decomposition (SVD) analysis, this work developed probability of exceedance streamflow forecasts for multiple stations, seasons, and lead-times. Forecasts were found to be generally skillful between the September-November and April-June seasons with this range narrowing as lead time increased and skill was mainly related to the impact of the El Niño-Southern Oscillation (ENSO) on the region. Using multiple indices of ENSO that were determined by correlation and composite analyses to track its evolution from the west Pacific at long lead-times to the east Pacific at short lead-times was not found to appreciably improve forecasts over using the Niño 3.4 index alone. Using SST expansion coefficient time-series from SVD analysis was found to capture the evolution of ENSO from west to east and to provide skillful forecasts of streamflow at earlier leads (up to 7 months in advance) compared to that found by pre-defined indices, indicating the importance of predictor selection in achieving optimal forecast skill.

A novel model to generate stochastic streamflow projections conditioned quasi-oscillatory climate indices – such as the Pacific Decadal Oscillation (PDO) the Atlantic Multi-decadal Oscillation (AMO), and the El Nino Southern Oscillation (ENSO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from an annually resolved, proxy based, paleo-reconstruction of each climate index and, the historical data covering the period from 1650-2012. A k-nearest neighbor, block bootstrap approach is then developed to simulate each of these climate index series, while preserving their time-frequency structure, and marginal distributions. Finally, given the simulated climate index time series, a k-nearest neighbor bootstrap is used to simulate annual streamflow series, conditional on the joint state space defined by ...

A highly resolved Mt. Everest ice core reveals a decrease in marine and increase in continental air masses related to relatively high summer surface pressure over Mongolia, and reduction in northward incursions of the summer South Asian monsoon since $1400 AD. Previously published proxy records from lower sites south of the Himalayas indicate strengthening of the monsoon since this time. These regional differences are consistent with a southnorth seesaw in convective activity in the Asian monsoon region, and reflect a southward shift in the mean summer position of the monsoon trough since $1400 AD. The change in monsoonal circulation at 1400 AD is synchronous with a reduction in solar irradiance and the onset of the LIA. This demonstrates a hemispheric scale circulation reorganization at this time, and the potential for future large shifts in monsoonal circulation.

The study forecasts the streamflow at a regional scale within SSJ river basin with largescale climate variables. The proposed approach eliminates the bias resulting from predefined indices at regional scale. The study was performed for eight unimpaired streamflow stations from 1962-2016. First, the Singular Valued Decomposition (SVD) teleconnections of the streamflow corresponding to 500 mbar geopotential height, sea surface temperature, 500 mbar specific humidity (SHUM 500), and 500 mbar U-wind (U 500) were obtained. Second, the skillful SVD teleconnections were screened non-parametrically. Finally, the screened teleconnections were used as the streamflow predictors in the non-linear regression models (K-nearest neighbor regression and data-driven support vector machine). New hydrological insights: The SVD results identified new spatial regions that have not been included in existing predefined indices. The nonparametric model indicated the teleconnections of SHUM 500 and U 500 being better streamflow predictors compared to other climate variables. The regression models were capable to apprehend most of the sustained low flows, proving the model to be effective for drought-affected regions. It was also observed that the proposed approach showed better forecasting skills with preprocessed large scale climate variables rather than using the predefined indices. The proposed study is simple, yet robust in providing qualitative streamflow forecasts that may assist water managers in making policy-related decisions when planning and managing watersheds.

Estimating long-lead time precipitation under the stress of increased climatic variability is a challenging task in the field of hydrology. A modified Support Vector Machine (SVM) based framework is proposed to estimate annual precipitation using oceanic-atmospheric oscillations. Oceanic-atmospheric oscillations, consisting of Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Niño-Southern Oscillation (ENSO) for a period of 1900-2008, are used to generate annual precipitation estimates with a 1 year lead time. The SVM model is applied to 17 climate divisions encompassing the Colorado River Basin in the western United States. The overall results revealed that the annual precipitation in the Colorado River Basin is significantly influenced by oceanic-atmospheric oscillations. The long-term precipitation predictions for the Upper Colorado River Basin can be successfully obtained using a combination of PDO, NAO, and AMO indices, whereas coupling AMO and ENSO results in improved precipitation predictions for the Lower Colorado River Basin. The results also show that the SVM model provides better precipitation estimates compared to the Artificial Neural Network and Multivariate Linear Regression models. The annual precipitation estimates obtained using the modified SVM modeling framework may assist water managers in statistically understanding the hydrologic response in relation to large scale climate patterns within the Colorado River Basin.

A systematic temporal and spatial analysis is being conducted at the U.S. EPA on historical precipitation and stream flow in the Lower Mississippi River basin (LMRB) and their relationships with Atlantic hurricanes and flooding events. The objectives are to decipher the periodicity and long-term trends exhibited in the hydroclimatic regime, and to determine their implications on the security of community water supplies in the region and the Gulf Coast, the parts of the continental U.S. prone to the negative impacts of extreme weather events under the current and future climate conditions. Statistical modeling using wavelet functions shows periodicity of continental precipitation and hurricanes with characteristic changes of trends around 1890-1900, 1940-1960, and the 1990s. These long-term decadal and multi-decadal changes were identified in a spatial modeling and wavelet frequency analysis of the 24-hour daily precipitation data obtained from the National Climatic Data Center. Long-term variations are also detected in hurricane and flooding events. Based on these findings, one can incorporate the hydroclimatic periodicity and long-term variations into the emergency water supply management and system designs. Measures such as water intake protection, using decentralized water supply, and planning emergency management are potential options in natural disaster preparedness. The results of the first phase investigation are discussed.