Atmospheric Circulation Indices Research Articles

Rain-Fed Rice Yield Fluctuation to Climatic Anomalies in Bangladesh

To examine the rain-fed Aman rice yield fluctuation due to climatic anomalies overtimes in Bangladesh, we used climate-induced yield index (CIYI), ensemble empirical mode decomposition (EEMD), step-wise multiple regression, isotopic signature, wavelet transform coherence (WTC) and random forest (RF) model. In this work, daily multiple source climatic data which were collected between 1980 and 2017, from 18 weather stations and five atmospheric circulation indices were used for this purpose. The key findings were as follows; by employing principal component analysis (PCA), six temporal variability modes were identified as six corresponding sub-regions with various Aman rice CIYI fluctuations. The Aman rice CIYI in different sub-regions represented a noteworthy 3–4-year quasi-oscillation using the EEMD. The key climate variables (KCVs) including the potential evapotranspiration and cloud cover in September, the minimum temperature in August, and precipitation in July, August, and October were the best rice yield prediction signals in these sub-regions. The results suggest that Aman rice yield could likely decline by 33.59%, and 3.37% in the southwestern and southeastern regions, respectively, if KCV increased by 1 °C or 1%. The RF model suggests that the Indian Ocean Dipole (IOD) significantly influenced the rice yield. Isotopic signatures were employed to confirm the fluctuation and anti-amount effect during the Aman rice-growing period in Bangladesh. The results obtained in this study could be used as a guideline for sustainable mitigation and adaptation measures in managing agro-meteorological hazards in Bangladesh.

Multi-century tree-ring anatomical evidence reveals increasing frequency and magnitude of spring discharge and floods in eastern boreal Canada

Abstract In eastern boreal Canada, variability in river discharge is poorly understood at the multi-century scale due to short instrumental records. In recent decades, increased magnitude and frequency of spring floods have raised concerns about the potential effects of climate change on flood risk. Unlike tree-ring width, flood rings have a demonstrated dendrochronological utility for reconstructing high discharge in boreal environments. In this study, twelve chronologies of earlywood vessel cross-sectional area (a new hydrological proxy) and ring width were developed from riparian Fraxinus nigra trees periodically flooded in spring. These chronologies were used as predictors of Harricana River spring discharge, which was reconstructed for the period 1771–2016. The reconstruction captured 69% of the variance over a 102-year calibration period. The reconstruction indicates that the magnitude and frequency of spring high discharge has increased since the end of the Little Ice Age (1850–1870 CE) and since 1950. The change from a multi-decadal frequency in the late 19th century to a decadal and then interannual frequency in the late 20th century is associated with an increase in snow cover over much of central-eastern Canada. The association between the reconstructed spring discharge and spring atmospheric circulation indices NINO3.4, AMO, NAO may also have changed in these periods and further work is needed to assess the stability of these associations. The correlation between reconstructed and instrumental spring discharge at the regional scale, as well as the shared features in reconstructed discharge and other paleorecords from subarctic Quebec suggest a common hydrological signal across the study area and for the early 20th to 21st centuries. The unprecedently low and high spring discharge in recent decades compared to the historical natural variability of the last 250 years also suggests that the increase in flood frequency and magnitude originates from climate change.

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

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

КЛИМАТИЧЕСКИЕ ИЗМЕНЕНИЯ НА ТЕРРИТОРИИ РОССИИ В КОНЦЕ ХХ - НАЧАЛЕ ХХI ВЕКА

The spatiotemporal variability of surface air temperature and precipitation in Russia is considered using the data from 1251 stations for two periods: 1976-2019 and 2001-2019. Main attention is paid to the analysis of trends in the above characteristics, which made it possible to estimate the scale of climate warming in recent decades. The connection between the atmospheric circulation indices (NAO, AO, EAWR, SCAND) and temperature fluctuations in the European part of Russia is revealed.

Influences of atmospheric circulation patterns on interannual variability of winter precipitation over the northern part of the Korean Peninsula

Explaining the relationship between atmospheric circulation patterns and precipitation over a given area is one of the key problems in predicting climate variables for monthly and seasonal leadtime. We investigated the influence of atmospheric circulation indices on winter precipitation over the northern part of the Korean Peninsula (WP-NPKP) during the period 1949-�2020. Data from 37 weather stations were used to calculate the correlation coefficients between WP-NPKP and the Siberian High (SH) and the Aleutian Low (AL), which are thought to dominate the winter weather systems over the study area. We chose those atmospheric circulation indices which are closely connected with the interannual variability of WP-NPKP and explained their possible mechanisms. To identify circulation patterns which most strongly correlated with WP-NPKP, one-point simultaneous correlation maps were created using Pearson correlation analysis, and their monotonic trends were tested with the Mann-Kendall method. We found that interannual variability of WP-NPKP had a closer connection with the difference in area-averaged climate variable anomalies over any 2 areas than with the anomalies themselves. Increased AL index minus decreased SH index had some correlation with winter rainfall; higher sea level pressure over the ocean, rather than that over land, was favorable for the transport of moisture toward the study area. Also, the indices which describe differences in air temperature anomalies at lower and middle latitudes had a relatively high correlation with WP-NPKP, and the difference indices of area-averaged zonal and meridional wind anomalies indicated a considerable linkage with winter precipitation over the study area. Their possible mechanisms, which we discuss in comparison to other studies of winter climate over East Asia, are very useful in selecting the predictors for monthly and seasonal prediction of climate variables over the study area.

ВЛИЯНИЕ МАКРОМАСШТАБНЫХ АТМОСФЕРНЫХ ПРОЦЕССОВ НА СЕЗОННЫЙ СТОК КРУПНЫХ СИБИРСКИХ РЕК

Based on daily runoff volumes of four large Siberian rivers (the Ob, Yenisei, Lena, and Kolyma) for 1936-2018, the regime and changes in the total annual and seasonal runoff are analyzed. High synchronous and asynchronous correlations between monthly river runoff and atmospheric circulation indices of hemispheric and regional scales are revealed. In recent decades, the total annual runoff and its variations have increased (the rate of increase is most pronounced for the Kolyma River). A change in water content within a year is heterogeneous: weak positive trends are characteristic of the spring flood runoff and the summer-autumn period, and a significant increase occurred in the winter months. High correlations with a 1-8-month shift made it possible to identify the most informative regions, the atmospheric circulation over which makes a certain contribution to the variance of river runoff.

Spatiotemporal variations of multi-scale drought in Shandong Province from 1961 to 2017

AbstractDrought has caused serious damage to the water resource system and agricultural production in Shandong Province, China. This study calculated the standardized precipitation evapotranspiration index (SPEI) based on the monthly precipitation and average temperature data of 25 meteorological stations in Shandong Province from 1961 to 2017. The trend analysis method and ArcGIS software were utilized to analyze the multi-scale (SPEI-1, SPEI-3, and SPEI-12) spatiotemporal changes of drought. The results revealed that (1) The intensity of drought showed an increasing trend in Shandong Province from 1961 to 2017; (2) The main periods of the drought on the seasonal scale (spring, summer, autumn, and winter) and annual scale were 8 years, 4 years, 15 years, 4 years, and 4 years, respectively; (3) Of the four seasons, the frequency of drought in autumn and winter were the highest. At the annual scale, the high-frequency drought areas were mainly concentrated in the southern mountainous regions; (4) In terms of the spatial change trend of drought, Shandong Province as a whole displayed a trend of becoming wet in the central and southwest regions and dry in the eastern region; and (5) Droughts were discovered to be simultaneously influenced by multiple atmospheric circulation indices in Shandong Province.

The role of blocking circulation and emerging open water feedbacks on Greenland cold‐season air temperature variability over the last century

AbstractSubstantial marine, terrestrial, and atmospheric changes have occurred over the Greenland region during the last century. Several studies have documented record‐levels of Greenland Ice Sheet (GrIS) summer melt extent during the 2000s and 2010s, but relatively little work has been carried out to assess regional climatic changes in other seasons. Here, we focus on the less studied cold‐season (i.e., autumn and winter) climate, tracing the long‐term (1873–2013) variability of Greenland's air temperatures through analyses of coastal observations and model‐derived outlet glacier series and their linkages with North Atlantic sea ice, sea surface temperature (SST), and atmospheric circulation indices. Through a statistical framework, large amounts of west and south Greenland temperature variance (up to r2 ~ 50%) can be explained by the seasonally‐contemporaneous combination of the Greenland Blocking Index (GBI) and the North Atlantic Oscillation (NAO; hereafter the combination of GBI and NAO is termed GBI). Lagged and concomitant regional sea‐ice concentration (SIC) and the Atlantic Multidecadal Oscillation (AMO) seasonal indices account for small amounts of residual air temperature variance (r2 < ~10%) relative to the GBI. The correlations between GBI and cold‐season temperatures are predominantly positive and statistically‐significant through time, while regional SIC conditions emerge as a significant covariate from the mid‐20th century through the conclusion of the study period. The inclusion of the cold‐season Pacific Decadal Oscillation (PDO) in multivariate analyses bolsters the air temperature variance explained by the North Atlantic regional predictors, suggesting the remote, background climate state is important to long‐term Greenland temperature variability. These findings imply that large‐scale tropospheric circulation has a strong control on surface temperature over Greenland through dynamic and thermodynamic impacts and stress the importance of understanding the evolving two‐way linkages between the North Atlantic marine and atmospheric environment in order to more accurately predict Greenland seasonal climate variability and change through the 21st century.

Changes in daily extreme temperature and precipitation events in mainland China from 1960 to 2016 under global warming

AbstractExtreme climatic events have become a global concern. Understanding changes in these events is essential to support efforts to reduce their impacts. We investigated the spatial and temporal variation of 15 temperature and 11 precipitation extremal indices based on daily observations from 1960 to 2016 at 794 meteorological stations in mainland China. The regionally averaged temperature index trends were consistent with global warming. An abrupt change in the trends for warmth‐related indices mainly occurred from 1990 to 2000, and the year with an abrupt change for cold‐related indices appeared earlier (mainly around 1990). The numbers of warm days, warm nights, summer days, and tropical nights increased significantly. In contrast, the numbers of cool days, cool nights, ice days, and frost days decreased significantly. The coldest night temperature had a strong and significant warming trend (0.4°C·decade−1), whereas the number of frost days showed the fastest decrease (2.6 days·decade−1). The warmth and extremal indices decreased significantly with increasing latitude, whereas warming trends increased significantly with increasing longitude, and the warmth indices and extremal daily indices decreased with increasing elevation. The number of consecutive wet days decreased fastest, at 0.09 days·decade−1, and the daily intensity index increased fastest, at 0.09 mm·day−1 per decade. The extreme precipitation events decreased significantly with increasing latitude, but increased with increasing longitude. Large‐scale atmospheric circulation indices (the Arctic Oscillation and the Western Pacific Subtropical High Intensity and Area indices) and the Western Ridge Point strongly influenced the warm and cold extremes and contributed significantly to climate change in mainland China. The Western Ridge Point and Subtropical High Area were the dominant drivers of extreme temperature and precipitation events, respectively, in mainland China.

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

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

Teleconnection patterns of precipitation in the Three-River Headwaters region, China

With the intensification of global warming, spatiotemporal variations in the climate and their mechanisms have received increasing attention. Currently, the relationship between regional precipitation regime, large-scale circulation, and topography, particularly in high-altitude areas such as the Qinghai–Tibet Plateau, are not well understood. Herein, the spatial and temporal variability in the annual and intra-annual (wet and dry periods) precipitation at 33 stations in the Three-River Headwaters (TRH) region from 1967 to 2016 are analysed. Moreover, the empirical orthogonal function and wavelet transform coherence methods are used to analyse the relationships between the different modes of precipitation change and 14 atmospheric circulation indices. The following results were obtained. (1) The mean annual precipitation and mean dry period precipitation significantly increased over the studied period. Annual and intra-annual precipitation showed a spatial southeast-to-northwest decreasing trend. (2) Two main patterns of precipitation were observed during the studied period: a dominant pattern with high- and low-value centres located in southeast and northwest TRH, respectively, and a dipole pattern with more precipitation over southwest TRH and less precipitation over northeast TRH. (3) Precipitation had a negative correlation with latitude, positive correlation with longitude, and nonlinear relationship with elevation. (4) Precipitation changes over various parts of the studied domain were determined based on changes in the weather systems affecting the area, with different indices being correlated with different components during different times of the year.

501 Years of Spring Precipitation History for the Semi-Arid Northern Iran Derived from Tree-Ring δ18O Data

In semi-arid regions of the world, knowledge about the long-term hydroclimate variability is essential to analyze and evaluate the impact of current climate change on ecosystems. We present the first tree-ring δ18O based hydroclimatic reconstruction for northern semi-arid Iran spanning the period 1515–2015. A highly significant correlation between tree-ring δ18O variations of juniper trees and spring (April–June) precipitation reveals a major influence of spring water availability during the early growing season. The driest period of the past 501 years occurred in the 16th century while the 18th century was the wettest, during which the overall highest frequency of wet year events occurred. A gradual decline in spring precipitation is evident from the beginning of the 19th century, pointing to even drier climate conditions. The analysis of dry/wet events indicates that the frequency of years with relatively dry spring increased over the last three centuries, while the number of wet events decreased. Our findings are in accordance with historical Persian disaster records (e.g., the severe droughts of 1870–1872, 1917–1919; severe flooding of 1867, the 1930s, and 1950). Correlation analyses between the reconstruction and different atmospheric circulation indices revealed no significant influence of large-scale drivers on spring precipitation in northern Iran.

Annual Runoff Forecasting Based on Multi-Model Information Fusion and Residual Error Correction in the Ganjiang River Basin

Accurate forecasting of annual runoff time series is of great significance for water resources planning and management. However, considering that the number of forecasting factors is numerous, a single forecasting model has certain limitations and a runoff time series consists of complex nonlinear and nonstationary characteristics, which make the runoff forecasting difficult. Aimed at improving the prediction accuracy of annual runoff time series, the principal components analysis (PCA) method is adopted to reduce the complexity of forecasting factors, and a modified coupling forecasting model based on multiple linear regression (MLR), back propagation neural network (BPNN), Elman neural network (ENN), and particle swarm optimization-support vector machine for regression (PSO-SVR) is proposed and applied in the Dongbei Hydrological Station in the Ganjiang River Basin. Firstly, from two conventional factors (i.e., rainfall, runoff) and 130 atmospheric circulation indexes (i.e., 88 atmospheric circulation indexes, 26 sea temperature indexes, 16 other indexes), principal components generated by linear mapping are screened as forecasting factors. Then, based on above forecasting factors, four forecasting models including MLR, BPNN, ENN, and PSO-SVR are developed to predict annual runoff time series. Subsequently, a coupling model composed of BPNN, ENN, and PSO-SVR is constructed by means of a multi-model information fusion taking three hydrological years (i.e., wet year, normal year, dry year) into consideration. Finally, according to residual error correction, a modified coupling forecasting model is introduced so as to further improve the accuracy of the predicted annual runoff time series in the verification period.

Inter‐annual variability in snow cover depletion patterns and atmospheric circulation indices in the Upper Irtysh basin, Central Asia

AbstractThe Irtysh River is the main water resource of Eastern Kazakhstan and its upper basin is severely affected by spring floods each year, primarily as a result of snowmelt. Knowledge of the large‐scale processes that influence the timing of these snow‐induced floods is currently lacking, but critical for the management of water resources in the area. In this study, we evaluated the variability in winter–spring snow cover in five major sub‐basins of the Upper Irtysh basin between 2000 and 2017 as a possible explanatory factor of spring flood events, assessing the time of peak snow cover depletion rate and snow cover disappearance from the moderate‐resolution imaging spectroradiometer (MODIS) MOD10A2 data set. We found that on average, peak snow cover retreat occurs between 22 March and 14 April depending on the basin, with large interannual variations but no clear trend over the MODIS period, while our comparative analysis of longer‐term snow cover extent from the National Oceanic and Atmospheric Administration Climate Data Record data set suggests a shift to earlier snow cover disappearance since the 1970s. In contrast, the annual peak snow cover depletion rate displays a weak increasing trend over the study period and exceeded 5,900 km2/day in 2017. The timing of snow disappearance in spring shows significant correlations of up to 0.82 for the largest basin with winter indices of the Arctic Oscillation (AO) over the region. The primary driver is the impact of the large‐scale pressure anomalies upon the mean spring (MAM) air temperatures and resultant timing of snow cover disappearance, particularly at elevations 500–2,000 m above sea level. This suggests a lagged effect of this atmospheric circulation pattern in spring snow cover retreat. The winter AO index could therefore be incorporated into long‐term runoff forecasts for the Irtysh. Our approach is easily transferable to other similar catchments and could support flood management strategies in Kazakhstan and other countries.

Improvements in Circumpolar Southern Hemisphere Extratropical Atmospheric Circulation in CMIP6 Compared to CMIP5

AbstractOne of the major globally relevant systematic biases in previous generations of climate models has been an equatorward bias in the latitude of the Southern Hemisphere (SH) mid‐latitude tropospheric eddy driven westerly jet. The far‐reaching implications of this for Southern Ocean heat and carbon uptake and Antarctic land and sea ice are key reasons why addressing this bias is a high priority. It is therefore of primary importance to evaluate the representation of the SH westerly jet in the latest generation of global climate and earth system models that comprise the Coupled Model Intercomparison Project Phase 6 (CMIP6). In this paper we assess the representation of major indices of SH extratropical atmospheric circulation in CMIP6 by comparison against both observations and the previous generation of CMIP5 models. Indices assessed are the latitude and speed of the westerly jet, variability of the Southern Annular Mode (SAM), and representation of the Amundsen Sea Low (ASL). These are calculated from the historical forcing simulations of both CMIP5 and CMIP6 for time periods matching available observational and reanalysis data sets. From the 39 CMIP6 models available at the time of writing there is an overall reduction in the equatorward bias of the annual mean westerly jet from 1.9° in CMIP5 to 0.4° in CMIP6 and from a seasonal perspective the reduction is clearest in austral spring and summer. This is accompanied by a halving of the bias of SAM decorrelation timescales compared to CMIP5. However, no such overall improvements are evident for the ASL.

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

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

ANALYSIS OF CHANGES IN TEMPERATURE AND HUMIDITY REGIME IN THE REPUBLIC OF BASHKORTOSTAN IN RECENT PERIOD

The article presents an analysis of the climatic characteristics of the regimes of air temperature and precipitation in the Republic of Bashkortostan in the period 1966-2015. For this period, the basic climatic characteristics are calculated. To identify changes in the analyzed values, trend analysis was used. Cases of air temperature anomalies and precipitation totals are examined in detail according to the criteria of intensity and duration of their existence for different time periods. Assessment of the influence of circulation factors on the indicators of the temperature-humidity regime of the region was carried out using a correlation analysis between them and the atmospheric circulation indexes - North Atlantic, Arctic, Scandinavian, Atlantic multi-decade oscillations.

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

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

Trends in cooling and heating degree-days overtimes in Bangladesh? An investigation of the possible causes of changes

An understanding of the trend in cooling and heating degree-days acts as a driving force for building energy demand under climate change conditions. However, little is known about the spatiotemporal trend patterns in cooling and heating degree-days in recent times and their possible causes in Bangladesh. Therefore, we explored the trend and variability of cooling degree-days (CDD) and heating degree-days (HDD) and their possible reasons for variation for the study period 1980–2017 based on daily temperatures datasets from 27 sites in Bangladesh. The results show that the highest annual mean CDD and HDD were identified in the southwestern and central climatic regions of Bangladesh. The CDD trend has significantly increased in Bangladesh, and the HDD trend has increased but non-significance. The outcomes of detrended fluctuation analysis (DFA) and R/S analysis exhibit that CDD and HDD will continue their contemporary trend direction in the future. Land–Ocean Temperature Index (LOTI) had a significant positive influence on CDD; however, there was no significant correlation between HDD and atmospheric circulation indices. The importance analysis from the random forest (RF) model showed that the LOTI is the highest contributing variable for CDD and East Asian Summer Monsoon Index (EASMI) is the largest influential variable for HDD affecting climate variability in Bangladesh. ECMWF ERA5 reanalysis datasets depict that higher summer geopotential height, an anticyclonic center, enhanced relative humidity, declined total and high cloud covers, decreasing surface solar radiation, and high skin temperature fluxes might have influenced on CDD and HDD variations in Bangladesh.

Spatiotemporal Variability of Precipitation in Beijing, China during the Wet Seasons

To comprehensively evaluate the changes in precipitation patterns in the context of global climate change and urbanization, the spatiotemporal variability of precipitation during the wet seasons of 1981–2017 in Beijing was analyzed in this study using up-to-date daily and hourly precipitation data from observation stations. It was concluded that the average annual precipitation in wet seasons showed a downward trend, while the simple daily intensity index (SDII) showed an upward trend. Precipitation in the central urban area of Beijing showed obvious changes from 1981 to 2017; the average annual precipitation in the central urban area was almost as great as that in Miyun country after 2010, which was the storm center for the past three decades. The average annual maximum 3-h and 6-h precipitation in the 2010s was higher than the past three decades, especially in urban and suburban areas. In addition, the atmospheric circulation index, urbanization impact, and topography were all found to be important factors that affect the pattern of precipitation in Beijing.