NCEP NCAR Reanalysis Research Articles

Seasonal Variability of Ice Motion for Hubbard and Valerie Glaciers, Alaska

Hubbard Glacier is a large fast-flowing tidewater-terminating glacier in the St. Elias Mountains and is connected at its terminus to Valerie Glacier. Although Hubbard Glacier has been shown to experience large intra-annual velocity changes and a long-term deceleration, previous seasonality studies have had limited timescale without a dense record of motion. Valerie Glacier’s variability has also been understudied, with only one study reporting its seasonal behaviour. The goal of this study was to combine ITS_LIVE, RADARSAT-2, RADARSAT Constellation Mission, and TerraSAR-X/TanDEM-X derived velocity data to create the densest record of motion ever constructed for Hubbard and Valerie glaciers from July 2013-April 2022 in order to explore seasonal velocity variability of both glaciers. Air temperature (NCEP-NCAR Reanalysis) was used to estimate surface melt on the glaciers, which was explored as a potential driver for seasonal velocity changes. Valerie Glacier had a seasonal pattern of fast flow in May, with minimum flow between August-November before accelerating again. Hubbard Glacier displayed a unique seasonal pattern that has not been previously observed on this glacier, with two periods of fast motion: one in May and one in December-February. It is inferred that the spring peaks and late summer/fall minimums on both glaciers are due to meltwater reaching the glacier bed and influencing the subglacial hydrology. The cause of the winter peak and slight velocity drop before the spring peak on Hubbard Glacier has not been determined and should be a topic for future studies, although it is hypothesized to influenced by its geometry.

Synoptic Analysis of Flood-Causing Rainfall and Flood Characteristics in the Source Area of the Yellow River

The source area of the Yellow River (SAYR) in China is an important water yield and water-conservation area in the Yellow River. Understanding the variability in rainfall and flood over the SAYR region and the related mechanism of flood-causing rainfall is of great importance for the utilization of flood water resources through the optimal operation of cascade reservoirs over the upper Yellow River such as Longyangxia and Liujiaxia, and even for the prevention of flood and drought disasters for the entire Yellow River. Based on the flow data of Tangnaihai hydrological station, the rainfall data of the SAYR region and NCEP-NCAR reanalysis data from 1961 to 2020, three meteorological conceptual models of flood-causing rainfall—namely westerly trough type, low vortex shear type, and subtropical high southwest flow type—are established by using the weather-type method. The mechanism of flood-causing rainfall and the corresponding flood characteristics of each weather type were investigated. The results show that during the process of flood-causing rainfall, in the westerly trough type, the mid- and high-latitude circulation is flat and fluctuating. In the low vortex shear type, the high pressures over the Ural Mountains and the Okhotsk Sea are stronger compared to other types in the same period, and a low vortex shear line is formed in the west of the SAYR region at the low level. The rain is formed during the eastward movement of the shear line. In the subtropical high southwest flow type, the low trough of Lake Balkhash and the subtropical high are stronger compared to other types in the same period. Flood-causing rainfall generally occurs in areas with low-level convergence, high-level negative vorticity, low-level positive vorticity, convergence of water vapor flux, a certain amount of atmospheric precipitable water, and low-level cold advection. In terms of flood peak increment and the maximum accumulated flood volume, the westerly trough type has a long duration and small flood volume, and the low vortex shear type and the subtropical high southwest flow type have a short duration and large flood volume.

Equatorward shift of ENSO-related subtropical jet anomalies in recent decades

Using observations, NCEP-NCAR and ERA5 reanalysis datasets, numerical experiments and CMIP6 model outputs, this study investigates long-term changes in the meridional position of subtropical jet anomalies in association with El Niño-Southern Oscillation (ENSO). It is found that the subtropical jet anomalies associated with ENSO index (i.e., Niño3.4 index in this study) over both Northern Hemisphere (NH) and Southern Hemisphere (SH) significantly (at the 99% confidence level) shift equatorward since the 1960s, at the speeds of 1.28 and 1.00° per decade, respectively. In recent six decades, the subtropical jet anomalies have moved equatorward by 4.34 and 3.19° over NH and SH, respectively. Our analysis indicates that the tropical positive sea surface temperature (SST) anomalies associated with Niño3.4 (corresponding to its warm phase) during 1990–2020 (P2) are weaker than those during 1950–1980 (P1). The weak, positive SST anomalies induce tropical weak, positive surface latent heat flux and precipitation anomalies, which heat tropical troposphere and produce weak, positive geopotential height anomaly with a narrow meridional width over the tropics during P2. According to geostrophic wind relations, anomalous positive zonal winds occur over the subtropics in the upper troposphere, meaning strengthened subtropical westerly jets over NH and SH. Hence, the relatively weak, narrow positive geopotential height anomaly during P2 favors the equatorward shift of Niño3.4-related subtropical jet anomalies via geostrophic wind relations. The results from numerical experiments and CMIP6 model outputs also indicate that changes in tropical SST anomalies associated with Niño3.4 contribute to this equatorward shift, supporting the results from reanalysis datasets. These results suggest that the intensity of tropical SST anomalies linked to ENSO should be well resolved to better simulate and predict subtropical jet variations.

Two Types of Mid-High-Latitude Intraseasonal Oscillations in the Southern Hemisphere during Austral Summer

Abstract Using NCEP–NCAR reanalysis data, the atmospheric intraseasonal oscillation (ISO) over the mid-high latitudes in the Southern Hemisphere during austral summer is studied. Two types of 10–30-day eastward- and westward-propagating ISO at mid-high latitudes are extracted by extended empirical orthogonal functions. The analysis of wave activity flux reveals that the energy sources of the eastward-propagating wave train are in the southwest Pacific and southern Indian Ocean, and the westward-propagating wave train is over the east coast of South America. The diagnosis of geopotential height tendency shows that the zonal gradient of ISO relative vorticity guided by mean zonal wind plays a major role in the eastward propagation of the wave train, while the meridional gradient of mean relative vorticity and geostrophic vorticity guided by ISO meridional wind plays a major role in the westward propagation of the wave train. Energy analysis shows that the amplitude enhancement over the South Pacific is due to the ISO disturbance gaining energy from the mean flow. The eastward-propagating ISO obtains energy from the mean flow through kinetic and potential energy conversion, while the westward-propagating ISO cannot obtain energy through potential energy conversion. The surface air temperature and precipitation in South America are affected by the circulation and propagation corresponding to both types of ISO. The useful forecasting skills by the subseasonal-to-seasonal forecasting project for eastward- and westward-propagating types can reach to 17 days, while the potential forecasting skills improve to 20 and 19 days, respectively. Significance Statement The intraseasonal oscillation (ISO) has important effects on regional weather and climate, and we focus on the ISO over mid-high latitudes in the Southern Hemisphere, which has been paid little attention. We reveal two leading types of the mid-high-latitude ISO during austral summer, namely, the eastward- and westward-propagating types. Also, the characteristics and effects of the two types are explored. To understand their dynamical process, the geopotential height tendency and energy conversion are diagnosed. It is also found that the two ISO types can be predicted up to 17 days in advance by the subseasonal-to-seasonal project, which may provide guidance for the extended-range forecasts.

Assessment of atmospheric emissivity models for clear-sky conditions with reanalysis data

Atmospheric longwave downward radiation (Ld) is one of the significant components of net radiation (Rn), and it drives several essential ecosystem processes. Ld can be estimated with simple empirical methods using atmospheric emissivity (εa) submodels. In this study, eight global models for εa were evaluated, and the best-performing model was calibrated on a global scale using a parametric instability analysis approach. The climatic data were obtained from a dynamically consistent scale resolution of basic atmospheric quantities and computed parameters known as NCEP/NCAR reanalysis (NNR) data. The performance model was evaluated with monthly average values from the NNR data. The Brutsaert equation demonstrated the best performance, and then it was calibrated. The seasonal global trend of the Brutsaert equation calibrated coefficient ranged between 1.2 and 1.4, and the K-means analysis identified five homogeneous zones (clusters) with similar behavior. Finally, the calibrated Brutsaert equation improved the Rn estimation, with an error reduction, at the worldwide scale, of 64%. Meanwhile, the error reduction for each cluster ranged from 18 to 77%. Hence, Brutsaert’s equation coefficient should not be considered a constant value for use in εa estimation, nor in time or location.

Indonesian Throughflow Partitioning between Leeuwin and South Equatorial Currents

Abstract Indonesian Throughflow (ITF) waters move along multiple pathways within the Indian Ocean. The western route is within the thermocline of the South Equatorial Current (SEC), and the southern route is via injection into the Leeuwin Current (LC) along western Australia. We use gridded Argo data to examine heat content anomaly (HCa) within three boxes in the eastern Indian Ocean, one adjacent to the ITF outflow from the Indonesian Seas (ITF box), the second in the eastern portion of the SEC (SEC box), and the third in the LC (LC box). Although interannual HCa variability in the SEC and ITF boxes is well correlated, a large increase in HCa within the ITF box does not appear in the SEC box in 2011 but is evident in the LC box. The 2011 change in the SEC–LC partitioning is investigated using GODAS reanalysis by examining the strength of the SEC and LC during a 2009 HCa increase within the ITF box and the subsequent increase in 2011. During 2009, a strong SEC and weakened LC spread the increased ITF HCa into the central Indian Ocean, whereas a weak SEC and strengthened LC during 2011 transmit the HCa signal to the south. Near-surface winds and mean sea level pressure from NCEP–NCAR reanalysis reveal that Ningaloo Niño events led to shifts in ocean circulation during 2000 and 2011. LC and SEC exports show a high negative correlation at interannual time scales, indicating that a reduction of outflow from one pathway is partially compensated by an increase from the other.

Meteorological Driving Datasets for the U.S. Midwest and Great Lakes Region Incorporating Precipitation Gauge Undercatch Corrections

Abstract Precipitation (P) gauge undercatch (PUC) is an important source of error when using observed meteorological datasets for hydrologic modeling studies in regions with cold and windy winters. Preliminary simulations using the Variable Infiltration Capacity (VIC) hydrological model forced with different meteorological datasets showed significant underprediction of simulated streamflow throughout the domain. A new hybrid gridded meteorological dataset at 1/16° resolution based on observed station data was assembled over the U.S. Midwest and Great Lakes region from 1915 to 2021 at a daily time step. Correction of primary station data using existing techniques is generally difficult or infeasible in the United States due to missing station metadata and lack of local wind speed (WS) measurements. We developed and tested several different postprocessing adjustment techniques using regridded WS obtained from the NCEP–NCAR reanalysis. The most effective approach corrected rain or mixed P using WS alone, and P as snow using a regressed snow-to-P ratio from a group of wind-shielded reference stations (to account for different and generally unknown snow measurement techniques). The PUC-corrected gridded products were validated against high-quality shielded stations and corrected Global Historical Climatology Network stations with in situ WS, showing good overall agreement. Observed monthly streamflow at 40 river basins was also compared to hydrologic model simulations forced by datasets with and without PUC corrections. The best PUC-corrected dataset produced improvements in streamflow simulations in at least 80% of the streamflow locations for three validation metrics (r2, Nash–Sutcliff efficiency, bias in the mean), demonstrating its value for hydrometeorological studies in the greater Midwest region. Significance Statement Many applications in hydrology require in situ precipitation (P) measurements, which are known to have a systematic low bias due to the effects of wind, also known as precipitation undercatch (PUC). Addressing PUC is problematic in the United States due to limited access to detailed station metadata (SMD) and local wind speed (WS) measurements. In this paper we develop a set of procedures to create gridded precipitation datasets for the U.S. Midwest region that incorporate corrections for PUC without needing either (i) detailed SMD or (ii) local WS measurements. Among other tests, results in 40 test basins throughout the Midwest show substantial improvements in simulated streamflow in 32 out of 40 basins when PUC corrections are included in meteorological driving datasets.

Large-scale background and role of quasi-biweekly moisture transport in the extreme Yangtze River rainfall in summer 2020

A severe flooding hit southern China along the Yangtze River in summer 2020. The floods were induced by extreme rains, and the associated dynamic and thermodynamic conditions are investigated using daily gridded rainfall data of China and NCEP-NCAR reanalysis. It is found that the June–July rainfall over the Yangtze River Basin (YRB) experienced pronounced subseasonal variation in 2020, dominated by a quasi-biweekly oscillation (QBWO) mode. The southwestward-moving anomalous QBWO circulation was essentially the fluctuation of cold air mass related to the tropospheric polar vortex or trough-ridge activities over the mid-high latitude Eurasian in boreal summer. The southwestward-transport of cold air mass from mid-high latitudes and the northeastward-transport of warm and moist air by the strong anomalous anticyclone over the western North Pacific provided important large-scale circulation support for the extreme rainfall in the YRB. The analysis of streamfunction of water vapor flux demonstrates that a large amount of water vapor eastward zonal transport from the Bay of Bengal and Indo-China and northward transport from the South China Sea provided the background moisture supply for the rainfall. The quasi-biweekly anomalies of potential and divergent component of vertically integrated water vapor flux played an important role in maintaining the subseasonal variability of rainfall in June–July of 2020. The diagnosis of moisture tendency budget shows that the enhanced moisture closely related to the quasi-biweekly fluctuated rainfall was primarily attributed to the moisture convergence. Further analysis of time-scale decomposition in the moisture convergence indicates that the convergence of background mean specific humidity by the QBWO flow and convergence of QBWO specific humidity by the mean flow played dominant roles in contributing to the positive moisture tendency. In combination with adiabatic ascent over the YRB induced by the warm temperature advection, the boundary layer moisture convergence strengthened the upward transport of water vapor to moisten the middle troposphere, favoring the persistence of rainfall during June–July. The vertical moisture transport associated with boundary layer convergence was of critical importance in causing low-level tropospheric moistening. By comparison, the horizontal moisture advection played a secondary important role in the quasi-biweekly oscillation of rainfall in June–July 2020.

A Self-Organizing Maps Analysis of Wintertime North Pacific Jet Stream Variability

Abstract Previous research regarding the intraseasonal variability of the wintertime Pacific jet has employed empirical orthogonal function (EOF)/principal component (PC) analysis to characterize two leading modes of variability: a zonal extension or retraction and a ∼20° meridional shift of the jet exit region. These leading modes are intimately tied to the large-scale structure, sensible weather phenomena, and forecast skill in and around the vast North Pacific basin. However, variability within the wintertime Pacific jet and the relative importance of tropical and extratropical processes in driving such variability, is poorly understood. Here, a self-organizing maps (SOM) analysis is applied to 73 Northern Hemisphere cold seasons of 250-hPa zonal winds from the NCEP–NCAR reanalysis data to identify 12 characteristic physical jet states, some of which resemble the leading EOF Pacific jet patterns and combinations of them. Examination of teleconnection patterns such as El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) provide insight into the varying nature of the 12 SOM nodes at inter- and intraseasonal time scales. These relationships suggest that the hitherto more common EOF/PC analysis of jet variability obscures important subtleties of jet structure, revealed by the SOM analysis, which bear on the underlying physical processes associated with Pacific jet variability as well as the nature of its downstream impacts.

Madden–Julian Oscillation Impacts on Australian Temperatures and Extremes

Abstract We assess seasonally varying impacts of the Madden–Julian oscillation (MJO) on Australian maximum and minimum temperature anomalies and extremes, and their modulation by El Niño–Southern Oscillation (ENSO), for the period June 1974–May 2022. Our composite-based approach uses observed temperatures from the Australian Gridded Climate Data, and 850-hPa wind data from the NCEP–NCAR reanalysis, to show how relationships to temperature and circulation evolve over the eight-phase life cycle of the MJO, which we derive from the real-time multivariate MJO index. The MJO has significant impacts on Australian temperatures and winds in all parts of the country at various times throughout the year, and to varying degrees. Two of the most pronounced impacts are 1) daytime warming across southeastern Australia in MJO phase 3 during spring associated with a strong anomalous anticyclone and 2) nighttime cooling over Queensland in MJO phase 7 during winter associated with anomalous advection of cool dry continental air. La Niña acts to significantly lessen both of these impacts, while El Niño enhances both the phase 3 warming over southern Australia in spring and the phase 7 overnight cooling over southern Queensland in winter. We show how the MJO can combine with El Niño and La Niña to have strong compounding influences, thus highlighting the importance of understanding interactions between multiple modes of climate variability and how they relate to Australian temperatures and extremes.

Annual Frequency of Tropical Cyclones Directly Affecting Guangdong Province:Prediction Based on LSTM-FC

Tropical cyclone (TC) annual frequency forecasting is significant for disaster prevention and mitigation in Guangdong Province. Based on the NCEP-NCAR reanalysis and NOAA Extended Reconstructed global sea surface temperature (SST) V5 data in winter, the TC frequency climatic features and prediction models have been studied. During 1951-2019, 353 TCs directly affected Guangdong with an annual average of about 5.1. TCs have experienced an abrupt change from abundance to deficiency in the mid to late 1980 with a slightly decreasing trend and a normal distribution. 338 primary precursors are obtained from statistically significant correlation regions of SST, sea level pressure, 1000hPa air temperature, 850hPa specific humidity, 500hPa geopotential height and zonal wind shear in winter. Then those 338 primary factors are reduced into 19 independent predictors by principal component analysis (PCA). Furthermore, the Multiple Linear Regression (MLR), the Gaussian Process Regression (GPR) and the Long Short-term Memory Networks and Fully Connected Layers (LSTM-FC) models are constructed relying on the above 19 factors. For three different kinds of test sets from 2010 to 2019, 2011 to 2019 and 2010 to 2019, the root mean square errors (RMSEs) of MLR, GPR and LSTM-FC between prediction and observations fluctuate within the range of 1.05-2.45, 1.00-1.93 and 0.71-0.95 as well as the average absolute errors (AAEs) 0.88-1.0, 0.75-1.36 and 0.50-0.70, respectively. As for the 2010-2019 experiment, the mean deviations of the three model outputs from the observation are 0.89, 0.78 and 0.56, together with the average evaluation scores 82.22, 84.44 and 88.89, separately. The prediction skill comparisons unveil that LSTM-FC model has a better performance than MLR and GPR. In conclusion, the deep learning model of LSTM-FC may shed light on improving the accuracy of short-term climate prediction about TC frequency. The current research can provide experience on the development of deep learning in this field and help to achieve further progress of TC disaster prevention and mitigation in Guangdong Province.

The interdecadal variations and causes of the relationship between Autumn Precipitation Anomalies in Eastern China and SSTA over the Southeastern tropical Indian Ocean

Eastern China has a large population with rapid development of the economy, where is the important crop producing region. In this region, the spatial and temporal distribution of autumn rainfall in Eastern China is uneven, which has important societal impact. Using the NCEP–NCAR reanalysis and other observational datasets, it is found that the spatial distribution of the first EOF mode of autumn rainfall anomalies in eastern China is consistent across the region, with significant interannual variabilities. Pronounced interdecadal variations are presented in the relationship between autumn rainfall anomalies in eastern China and sea-surface temperature anomaly (SSTA) over the southeastern tropical Indian Ocean (SETIO). The interdecadal changes have been analyzed by considering two epochs: one during 1979–2004 and the other during 2005–2019. It shows weak and insignificant correlations between the autumn rainfall anomalies in eastern China and SSTA over SETIO during the first epoch. On the other hand, they are remarkable and positively correlated with each other during the second epoch. The inter-decadal changes of the above relationship are related to the warming of SST over SETIO during the second epoch. It causes stronger low-level convergence and ascending motion over SETIO, with the co-occurrence of enhanced western Pacific subtropical high and anomalous abundant moisture over eastern China carried by a low-level southerly anomaly originating from the South China Sea. Simultaneously, the local Hadley circulation over eastern China becomes weak, corresponding to the anomalous ascending motion. The collaboration of anomalous water vapour transport and ascending motion strengthens the connection between the SETIO SSTA and the autumn precipitation anomalies in eastern China, and vice versa. In the boreal autumn of 2019, entire eastern China suffered extreme drought. It suggests that this drought event in eastern China is strongly affected by the negative SSTA over SETIO, which is consistent with the statistical results.

Synoptic Climatology of Air Temperatures behind Extreme Cyclone Events over the Bay of Bengal of Southern Bangladesh

Cyclones have occurred more frequently in recent decades in a disaster-prone country like Bangladesh. Twenty-two (22) extreme cyclone events that occurred from 1975-2014 were investigated in this study with respect to air temperature climatology. Air temperature, sea level pressure, rainfall, relative humidity (Rhum), and sunshine hours (SShr) have been analyzed to find out the impact of air temperatures behind cyclogenesis. Historical cyclone data were obtained from Bangladesh Meteorological Department; Bangladesh Bureau of Statistics and Disaster Preparedness Centre (AIT). Historical weather data was collected from the Climate Division of BMD. Principal Component Analysis (PCA) and Clustering were used to find out the whole atmospheric air temperature impact on cyclogenesis. The NCEP–NCAR reanalysis data were used to find out the distribution of air temperature anomaly over Bangladesh and Bay of Bengal (BB). Among the 22 cyclones, cluster 2 belongs to 9 cyclones and cluster 3 comprises of 12 cyclones. Clusters 2 and 3 indicate that temperatures of about 34 to 35°C were mostly responsible for the formation of a total of 21 cyclones from 1975 to 2014. The existence of a relatively cooler zone (strong negative anomaly) near to surface level, in association with a relatively warmer zone (strong positive anomaly) at 850, 700, 500, and 300hPa level were firmly responsible for cyclogenesis over BB. The larger, warmer air mass in the upper atmosphere could have a significant impact on the development of huge instability throughout the entire atmospheric column, potentially leading to the formation of extreme weather phenomena such as severe cyclones in southern Bangladesh.

Using and Evaluating the Efficiency of GRIMs Model in Making Some Simulations of Weather Variables in Three Countries in Middle East: A Snowfall Case Study

Predicting weather by numerical models have been used extensively in research works for Middle East, mostly for dust storms, rain showers, and flash floods with a less deal of interest on snow precipitation. In this study, the Global/Regional Integrated Model System (GRIMs) that was developed in South Korea was used to predict a rare snowfall event occurred in three countries in Middle East (Syria, Jordan and Iraq) located between (25-65 oE; 12-42 oN) in year 2008. The main aim of this study was to test GRIMs efficiency, which would be used for the first time in Middle East, to make predictions of weather parameters such as pressure, temperature, and relative humidity especially in the selected area. In addition, the study would investigate the conditions that caused the snowfall event. GRIMs model was installed, compiled, and run on a Linux platform by using NCEP-NCAR reanalysis dataset as initial conditions on 0.5 × 0.5 grid resolution to make simulations for three days at intervals of three hours. The output of the model was evaluated by making comparisons with actual data obtained from the GFS Agency dataset and the model showed its efficiency. The snowfall event was synoptically discussed in details. It was found that the snowfall event was a result of fast succession systems of a strong cold high pressure and then a deep warm low pressure. The high instability in the region had led to form large cumuliform clouds with snow precipitation as a rare event in very long period.

Associated atmospheric mechanisms for the increased cold season precipitation over the Three-River Headwaters region from the late 1980s

AbstractPrecipitation in the Three-River Headwater (TRH) region has undergone significant changes as a result of global warming, which can affect water resources in downstream regions of Asia. However, the underlying mechanisms of the precipitation variability during the cold season (October to April), are still not fully understood. In this study, the daily China gridded precipitation product of CN05.1 as well as the NCEP-NCAR reanalysis are used to investigate the characteristics of the cold season precipitation variability over the TRH region and associated atmospheric mechanisms. The cold season precipitation shows an increasing trend (5.5 mm decade-1) from 1961 to 2014, with a dry-to-wet shift in around the late 1980s. The results indicate that the increased precipitation is associated with the enhanced easterly anomalies over the Tibetan Plateau (TP) and enhanced southeasterly water vapor transport. The enhanced Walker circulations, caused by the gradients of sea surface temperature between the equatorial central-eastern Pacific and Indo-western Pacific in tropical oceans, resulted in strengthened easterly anomalies over the TP and the westward expansion of the anticyclone in the western North Pacific. Meanwhile, the changed Walker circulation is accompanied by a strengthened local Hadley circulation which leads to enhanced meridional water vapor transport from tropical oceans and the South China Sea toward the TRH region. Furthermore, the strengthened East Asia Subtropical Westerly jet may contribute to the enhanced divergence at upper level and anomalous ascending motion above the TRH region leading to more precipitation.

Global oscillatory modes in high-end climate modeling and reanalyses

Interannual oscillatory modes, atmospheric and oceanic, are present in several large regions of the globe. We examine here low-frequency variability (LFV) over the entire globe in the Community Earth System Model (CESM) and in the NCEP-NCAR and ECMWF ERA5 reanalyses. Multichannel singular spectrum analysis (MSSA) is applied to these three datasets. In the fully coupled CESM1.1 model, with its resolution of 0.1 times 0.1 degrees in the ocean and 0.25 times 0.25 degrees in the atmosphere, the fields analyzed are surface temperatures, sea level pressures and the 200-hPa geopotential. The simulation is 100-year long and the last 66 yr are used in the analysis. The two statistically significant periodicities in this IPCC-class model are 11 and 3.4 year. In the NCEP-NCAR reanalysis, the fields of sea level pressure and of 200-hPa geopotential are analyzed at the available resolution of 2.5 times 2.5 degrees over the 68-years interval 1949–2016. Oscillations with periods of 12 and 3.6 years are found to be statistically significant in this dataset. In the ECMWF ERA5 reanalysis, the 200-hPa geopotential field was analyzed at its resolution of 0.25 times 0.25 degrees over the 71-years interval 1950–2020. Oscillations with periods of 10 and 3.6 years are found to be statistically significant in this third dataset. The spatio-temporal patterns of the oscillations in the three datasets are quite similar. The spatial pattern of these global oscillations over the North Pacific and North Atlantic resemble the Pacific Decadal Oscillation and the LFV found in the Gulf Stream region and Labrador Sea, respectively. We speculate that such regional oscillations are synchronized over the globe, thus yielding the global oscillatory modes found herein, and discuss the potential role of the 11-year solar-irradiance cycle in this synchronization. The robustness of the two global modes, with their 10–12 and 3.4–3.6 years periodicities, also suggests potential contributions to predictability at 1–3 years horizons.

Synoptic–Dynamic Patterns Affecting Iran’s Autumn Precipitation during ENSO Phase Transitions

We compared the effect on autumn (October, November, December) precipitation over Iran during two types of El Niño–Southern Oscillation (ENSO) phase transitions from the perspective of anomalies in wave activity flux and sea level pressure along the Atlantic–Mediterranean storm track, as well as precipitation. We used Oceanic Niño Index (ONI) to identify the transition phases of ENSO (El Niño to La Niña and also La Niña to El Niño, referred to as type 1 and type 2, respectively). Climate data during the period of 1950 to 2019 used in this study is derived from NCEP-NCAR reanalysis. In order to investigate the intensity and direction of Rossby wave trains in different ENSO transitions, we used the wave activity flux parameter, and to evaluate the statistical significance of values, we calculated Student’s t-test. The impact of the Atlantic storm track on the Mediterranean storm track was shown to be greater in type 2 transitions. Further, the existence of a stronger wave source region in the Mediterranean region during type 2 transitions was established. Results also showed the weakening of the Iceland low and Azores high pressure in type 1 transitions and the reinforcement of both in type 2, with the differences being significant at up to a 99% confidence level. Pressure values over Iran were at or below normal in type 1 years and below normal in type 2. Finally, the composite analysis of precipitation anomaly revealed that during ENSO type 1 transitions, most regions of Iran experienced low precipitation, while in type 2, the precipitation was more than average, statistically significant at 75% confidence level or higher over the northern half of the country.

The Shallowing Surface Temperature Inversions in the Arctic

AbstractTemperature inversions play an important role in various physical processes by affecting the atmospheric stability, regulating the development of clouds and fog, and controlling the transport of heat and moisture fluxes. In the past few decades, previous studies have analyzed the spatiotemporal variability of Arctic inversions, but few studies have investigated changes in temperature inversions. In this study, the changes in the depth of Arctic inversions in the mid-twenty-first century are projected based on a 30-member ensemble from the Community Earth System Model Large Ensemble (CESM-LE) project. The ERA-Interim, JRA-55, and NCEP–NCAR reanalysis were employed to verify the model results. The CESM-LE can adequately reproduce the spatial distribution and trends of present-day inversion depth in the Arctic, and the simulation is better in winter. The mean inversion depth in the CESM-LE is slightly underestimated, and the discrepancy is less than 11 hPa, within a reasonable range. The model results show that during the mid-twenty-first century, the inversion depth will strongly decrease in autumn and slightly decrease in winter. The shallowing of the inversion is most obvious over the Arctic Ocean, and the maximum decrease is over 65 hPa in the Pacific sector in autumn. In contrast, the largest decrease in the inversion depth, which is more than 45 hPa, occurs over the Barents Sea in winter. Moreover, the area where the inversion shallows is consistent with the area where the sea ice is retreating, indicating that the inversion depth over the Arctic Ocean in autumn and winter is likely regulated by the sea ice extent through modulating surface heat fluxes.

Analysis of rainfall variability over Tanzania in late austral summer

Based on site-observation data, NCEP–NCAR reanalysis data, and Climatic Research Unit gridded data, the rainfall variability over Tanzania during late austral summer (January–March, JFM) was analyzed for the period 1961–2011. Further, the associated atmospheric circulation and SST anomalies (SSTAs) were explored to understand the mechanisms of dry- and wet-year cases based on an interannual time scale. The correlation, Morlet wavelet power spectrum, and composite analysis methods were employed. The results showed that the JFM standardized rainfall anomaly time series exhibited significant time scales of variability at interannual (2–8 years) and quasi-decadal (8–12 years). During dry years, anomalous anticyclonic northeasterly flow originating from western tropical Indian and southeast trades from the Indian Ocean to the southeast were associated with subsiding dry air, which resulted in suppression of rainfall as observed. In the typical wet-year cases, meanwhile, anomalous westerlies from the tropical and southeast Atlantic were strengthened over the Congo basin, delivering more precipitation to the region. Significant correlation was exhibited over the western tropical and southeast Indian Ocean, as well as the southeast and tropical Atlantic Ocean. These SSTA patterns favored atmospheric general circulation anomalies that were closely related to JFM rainfall over Tanzania.摘要利用站点观测资料和再分析资料, 采用相关分析, Morlet小波功率谱分析和复合分析等方法, 研究了1961–2011年南半球夏季后期 (1–3月) 坦桑尼亚降水的年际变化特征, 并探讨了相关的大气环流和海温异常情况, 以及坦桑尼亚干,湿年发生的机制. 研究结果表明: 坦桑尼亚1–3月降水变化存在显著的2–8年的年际变化周期和8–12年准年代变化周期. 在坦桑尼亚1–3月降水异常偏少的典型干旱年, 来自热带西印度的异常反气旋的东北气流和北印度洋东南气流造成干燥空气下沉, 从而抑制坦桑尼亚地区降水; 而在典型多雨年, 来自非洲大陆热带和东南大西洋的异常西风气流在刚果盆地上空显著偏强, 从而带来更多降水. 热带印度洋和印度洋东南部, 大西洋东南部和热带大西洋均表现出显著的相关性. 此外, 热带中太平洋和南太平洋中部也存在显著的相关. 这些海温异常型与坦桑尼亚1–3月的降水及相关大气环流异常有密切的关联.

Synoptic processes over the Kodar glacier zone during the ablation period

The small glaciers of the Kodar ridge (south of Eastern Siberia), located inland Asia under the influence of both Atlantic and Pacific air transport, are the valuable objects for studying their response to changes in mid-latitude atmospheric circulation. However, detailed meteorological studies on the glaciers have been limited so far. For the first time, in July–August 2019, the meteorological characteristics were measured on the Sygyktinsky glacier using automatic weather station. We have analyzed the relationship between variations of large-scale atmospheric circulation and meteorological regime of the glacier using the NCEP–NCAR reanalysis data. During the observation period, Kodar was under the influence of a positive geopotential anomaly in the lower troposphere, which determined increased temperatures and decreased relative humidity and precipitation. Quasi-cyclic fluctuations in meteorological time series (e.g. air temperature) reflect the influence of large scale synoptic changes caused by the front passages, warm and cold air advections. High ablation rates on the glacier were associated with anticyclones, subtropical ridges, and warm air advections (from southeast and southwest), while decreased ablation was observed during the cyclone passage and cold air advection (from north, northeast, and west).