Winter Trends Research Articles

A regional (land–ocean) comparison of the seasonal to decadal variability of the Northern Hemisphere jet stream 1871–2011

Seasonal to decadal variations in Northern Hemisphere jet stream latitude and speed over land (Eurasia, North America) and oceanic (North Atlantic, North Pacific) regions are presented for the period 1871–2011 from the Twentieth Century Reanalysis dataset. Significant regional differences are seen on seasonal to decadal timescales. Seasonally, the jet latitude range is lower over the oceans compared to land, reduced from 20° over Eurasia to 10° over the North Atlantic where the ocean meridional heat transport is greatest. The mean jet latitude range is at a minimum in winter (DJF), particularly along the western boundary of the North Pacific and North Atlantic, where the land-sea contrast and SST gradients are strongest. The 141-year trends in jet latitude and speed show differences on a regional basis. The North Atlantic has significant increasing jet latitude trends in all seasons, up to 3° in winter. Eurasia has significant increasing trends in winter and summer, however, no increase is seen across the North Pacific or North America. Jet speed shows significant increases evident in winter (up to 4.7 ms−1), spring and autumn over the North Atlantic, Eurasia and North America however, over the North Pacific no increase is observed. Long term trends are generally overlaid by multidecadal variability, particularly evident in the North Pacific, where 20-year variability in jet latitude and jet speed are seen, associated with the Pacific Decadal Oscillation which explains 50% of the winter variance in jet latitude since 1940. The results highlight that northern hemisphere jet variability and trends differ on a regional basis (North Atlantic, North Pacific, Eurasia and North America) on seasonal to decadal timescales, suggesting that different mechanisms are influencing the jet latitude and speed. This is important from a climate modelling perspective and for climate predictions in the near and longer term.

Sensitivity of Green-Up Date to Meteorological Indicators in Hulun Buir Grasslands of China

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future.

The impacts of VOCs on PM2.5 increasing via their chemical losses estimates: A case study in a typical industrial city of China

Volatile organic compounds (VOCs) have been explicitly required to be controlled by national or local governments to tackle heavy PM2.5 pollution in China. However, the role of VOCs chemistry in PM2.5 is still far away from being fully understood. In this study, we selected a typically industrialized city of China, conducted VOCs online measurements in July and December of 2020, estimated VOCs chemical losses, and explored their impacts on PM2.5 in the real atmosphere. Our measurements totally detected the mixing ratios of 53 VOCs species, sum of which reaching 20.8 ± 9.1 ppb and 45.5 ± 19.8 ppb in July and December respectively. Based on the change in the relative abundance of various VOCs species with different reactivity, daily OH exposure and daily O3 exposure (molecules·s·cm−3) were estimated, respectively with the mean value of 11.0 × 1010 and 5.2 × 1015 in July, 5.9 × 1010 and 3.1 × 1015 in December. Thus, there were about 6.7 ± 3.2 ppb and 11.1 ± 5.0 ppb VOCs chemically lost in July and December, with the average loss ratio of 29.7% and 19.3% in respective. In July, PM2.5 in the range of 20–60 μg m−3 positively responded to VOCs loss ratios, and high PM2.5 values were always accompanied by higher VOCs losses instead of high CO levels; but their relationship became negative in December when PM2.5 in the range of 40–150 μg m−3, and extremely high PM2.5 values happened in high CO conditions instead of high VOCs losses conditions. Moreover, PM2.5 measurements in this city also showed an apparent upward trend in OC/EC with PM2.5 in summer, but a slight downward trend in winter. These all indicated that in the conditions of stronger solar radiations (summer) and low-middle aerosol loads, VOCs chemistry played the important role in PM2.5 increasing through contributing SOA; but in the conditions of lower solar radiations (winter) and heavy aerosol loads, VOCs chemistry was greatly weakened and had the minor impact on PM2.5 increasing. The measure involving VOCs reduction to alleviate PM2.5 pollution in winter needs to be cautiously considered and examined.

The Long-Term ERA5 Data Series for Trend Analysis of Rainfall in Italy

Nowadays, the Mediterranean region is generally recognized as a climate change hot spot given its strong response to global warming, with relevant impacts on rainfall amount and distribution. Within this context, in this work the temporal variability of rainfall at annual, seasonal and monthly scale was analyzed in Italy using rainfall data extracted from the reanalysis dataset ERA5-Land during the period 1950–2020. In particular, rainfall trend magnitude and significance have been estimated by means of non-parametric tests applied to 3215 grid points falling within the Italian territory. The main results of this analysis evidenced only a few relevant trends at the annual scale, mostly involving northern Italy (positive trend) and the Sardinia region (negative trend). At seasonal scale, the results showed a marked negative trend in winter, characterizing almost all the Italian territory, while in the other seasons a positive trend was identified in the majority of grid points, especially in the Alps. Finally, at the monthly scale, September was identified as the month of the year with the highest percentage of grid points with positive trends mainly located in central, southern, and north-eastern Italy.

Sea surface temperature trend analysis by Mann-Kendall test and sen’s slope estimator: a study of the Hai Phong coastal area (Vietnam) for the period 1995-2020

Based on the Mann-Kendall test and Sen’s slope method, this study investigates the monthly, seasonal, and annual sea surface temperature (SST) trends in the coastal area of Hai Phong (West of Tonkin Gulf) based on the measurements at Hon Dau Station from 1995 to 2020. The results show a sea surface warming trend of 0.02°C/year for the period 1995-2020 (significant level α = 0.1) and of 0.093°C/year for the period 2008-2020 (significant level α = 0.05). The monthly SSTs in June and September increased by 0.027°C/year and 0.036°C/year, respectively, for the period 1995-2020, and by 0.080°C/year and 0.047°C/year, respectively, for the period 2008-2020. SST trends in winter, summer, and other months were either different for the two periods or not significant enough. This may be due to the impact of ENSO, which caused interannual SST variability in the Hai Phong coastal with two intrinsic mode functions (IMF) signals a period of ~2 (IMF3) and ~5.2 years cycle (IMF4). A combination of these signals had a maximum correlation of 0.22 with ONI (Oceanic Niño Index) delayed by 8 months. ENSO events took ~8 months to affect SST at Hai Phong coastal area for 1995-2020 and caused a variation of SST within 1.2°C.

Long-term change in relative humidity across China from 1961-2018

Using observational data of daily relative humidity obtained from 2479 meteorological stations from 1961-2018 and the homogenized monthly data set of national ground meteorological stations, this paper analyzes the climate change characteristics of average relative humidity across China as well as in 9 individual regions. From 1961-2018, the climate change trend in annual average relative humidity across China was negligible, but there were large differences among different regions. Overall, annual relative humidity in the Qinghai-Tibet Plateau and Xinjiang area showed a significant increase, while Northwest China, Northeast China and northern North China showed a significant decrease. Seasonally, average relative humidity in China chiefly decreased in spring, and there was no discernable trend in other seasons. The Qinghai-Tibet Plateau showed a significantly increasing trend in winter, spring and summer, especially in spring; Xinjiang exhibited a significant increasing trend in winter, summer and autumn; Northeast China presented a significantly decreasing trend in winter; Northwest China, North China, Central China and East China witnessed a significantly decreasing trend in spring; and South China and Southwest China showed a slightly decreasing trend across all 4 seasons. Large urban agglomerations exert an influence on relative humidity to some degree, with urban areas experiencing lower relative humidity than rural areas.

Climate change impact assessment on low streamflows using cross-entropy methods

Climate change impacts on low streamflows provide a comprehensive picture of the state of surface and groundwater resources, particularly in arid and semi-arid regions. The objective of this study was to assess climate change impacts on low streamflow variations by detecting long-term spatio-temporal changes in climatic variables of rainfall and temperature, and their associations with low streamflow fluctuations. Seasonal variations in low streamflows (summer and winter) were examined at 18 hydrometric stations located in the Namak Lake basin, Iran, over 1970-2015, using the modified Mann-Kendall and Sen’s slope estimator methods. Seasonal low streamflow demonstrated a significant diminishing trend (more than 55% of the stations), while summer low streamflow showed a more drastic decreasing trend. Long-term changes in seasonal and annual rainfall/temperature also revealed a dominant decreasing trend in winter and spring rainfall (82% and 58% of all stations, respectively) and a dominant increasing trend in all temperature time scales (90% of all stations). The effects of climate variations on low streamflow were quantified by the Spearman’s rank correlation and Cross-SampEn methods. The results revealed that winter rainfall, and annual and summer temperatures have the strongest association with seasonal low streamflows, especially according to the entropy method. Although the relationships between low streamflows and temperature/rainfall are related to the different processes generating streamflows, particularly in heterogeneous locations, the results show that rainfall has a stronger influence on low streamflows in the study region than temperature does. The research findings indicate low streamflows are more nonlinearly related to climatic parameters, and Cross-SampEn robustness reflects degree of asynchrony for complex and non-stationary time series.

Analysis of Drought Characteristics and Its Effects on Crop Yield in Xinjiang in Recent 60 Years

With global warming, the frequency of drought in China is gradually increasing. The study of drought characteristics and its impact on crop yield is of great significance to ecological construction and food security. Based on the SPEI index in Xinjiang from 1961 to 2020, the changing characteristics of drought and their responses to meteorological yield of three kinds of crops (cotton, wheat and corn) were analyzed. The results revealed that the SPEI in Xinjiang exhibited a decreasing trend. Drought occurred less during 1961–1996 and mainly occurred during 1997–2020. The annual variation trend of SPEI decreased regionally, and the arid trend increased from northwest to southeast. The seasonal variation in SPEI displayed an increasing trend only in winter, but a decreasing trend in spring, summer and autumn. The decreasing trend of the SPEI index in spring accounted for 90.91%, mainly distributed in the central and eastern part of Xinjiang; the decreasing trend in summer accounted for 81.82%, mainly located in the eastern part of Xinjiang; the decreasing trend in autumn accounted for 84.85%, mainly located in the south and central and eastern part of Xinjiang; the decreasing trend in winter accounted for only 33.33%, mainly located in the southwest, central and eastern part of Xinjiang; the per unit area yield of the three kinds of crops showed a significant increasing trend (p < 0.01). The meteorological yield of cotton showed an increasing trend, while that of wheat and corn showed a decreasing trend. Correlation analysis of climatic yield and SPEI, and regression analysis of standardized climatic yield residuals and SPEI in different seasons revealed that drought in spring and autumn had the greatest effect on the meteorological yield of cotton, while drought in spring and summer had the greatest effect on the meteorological yield of wheat and corn.

Climate Change Characteristics of Coastal Wind Energy Resources in Zhejiang Province Based on ERA-Interim Data

The reanalysis of sea surface wind speed is compared with the measured wind speed of five offshore wind towers in Zhejiang, China. The applicability of reanalysis data in the Zhejiang coastal sea surface and the climatic characteristics of sea surface wind power density is analyzed. Results show that the reanalysis of wind field data at the height of 10 m can well capture the wind field characteristics of the actual sea surface wind field. The sea surface wind power density effective hours increases from west to east and north to south. Then Empirical orthogonal function (EOF) is used to analyze the sea surface wind power density anomaly field, and the first mode is a consistent pattern, the second mode is a North-South dipole pattern, the third mode is an East-West dipole pattern respectively. The stability of wind energy resources grows more stable with increasing distance from the coast, and the northern sea area which is far away from the coastal sea is more stable than that of the southern sea area. The yearly linear trend of sea surface wind power density is in an East-West dipole pattern respectively. The wind energy resources are more stable farther from the coast, and the wind energy resources in the northern sea are more stable than that of the southern sea. The yearly linear trend of sea surface wind power density is the East-West dipole type, the seasonal linear trend is a significant downward trend from West to East in spring, and on the contrary in summer, a non-significant trend in autumn and winter. The monthly change index shows that the linear trend near the entrance of Hangzhou Bay in Northern Zhejiang is of weak increase or decrease, which is good for wind energy development. When the wind power density is between 0 and 150 W·m−2, its frequency mainly shows the distribution trend of high in the West and low in the East, but the wind power density is between 150 and 600 W·m−2, its distribution is the opposite.

Impact of internal variability on recent opposite trends in wintertime temperature over the Barents–Kara Seas and central Eurasia

The large ensembles of the IPSL-CM6A-LR model output for the historical forcing experiment were employed to investigate the role of internal variability in the formation of the recent “warm Arctic–cold Eurasia” trend pattern in winter surface air temperature (SAT). The ensemble-mean SAT shows a positive trend over Arctic during 1990–2014, indicating a positive contribution of anthropogenic forcing to the warming Arctic. Over the region of central Eurasia, the ensemble-mean SAT trend is opposite to the observed trend. The winter SAT trends display remarkable inter-member diversity over the Barents–Kara Seas (BKS) region and central Eurasia, suggesting an important role played by internal variability. In addition to anthropogenic forcing, the results suggest that the barotropic anticyclone over northern Eurasia arising from internal variability can also contribute positively to the warming anomalies over the BKS region. On the other hand, through a fingerprint pattern matching method, it is found that the observed cooling trend over central Eurasia tends to be predominantly due to the internal variability. Finally, the results estimate that the internal variability can contribute to about 50–60% of the observed warming trend over the BKS region.

Assessing the impact of climate on annual and seasonal discharges at the Sremska Mitrovica station on the Sava River, Serbia

Abstract Flood frequency analysis was performed on annual maxima series for 90 years (1928–2017) of discharge data recorded at the Sremska Mitrovica gauging station on the Sava River. The three-parameter distributions (PearsonIII, Log-PearsonIII) are more suitable for modelling annual maxima than distribution functions with only two parameters (Normal, Log-normal, Gumbel). The Mann–Kendall test statistic indicated that there is no statistically significant trend identified in annual maximum discharges or average annual discharges. A positive increasing trend was observed in annual temperature, while annual precipitation shows a decreasing trend which is non-significant. The seasonality analysis found a statistically non-significant weak negative trend in discharge in spring, summer and autumn and a statistically non-significant weak positive trend in winter. During winter, spring, and summer a non-significant negative trend in precipitation was observed, while autumn has experienced a statistically significant increasing trend. Temperatures show a positive trend in all seasons, but only temperatures during the warm period show a statistically significant increase. The results demonstrate that decreasing discharges of the Sava River at the Sremska Mitrovica gauging station are mainly the consequence of decreasing precipitation and increasing temperature (increasing evaporation), which is consistent with the results of other studies of the region.

Effects of large-scale atmospheric circulation on the Baltic Sea wave climate: application of the EOF method on multi-mission satellite altimetry data

Wave heights in the Baltic Sea in the period 1992–2015 have mainly increased in the sea’s western parts. The linear trends in the winter wave heights exhibit a prominent meridional pattern. Using the technique of Empirical Orthogonal Functions (EOF) applied to multi-mission satellite altimetry data, we explain a large part of this increase with the Scandinavia pattern, North Atlantic Oscillation and Arctic Oscillation climatic indices. The winter trends show a statistically significant negative correlation (correlation coefficient –0.47 ± 0.19) with the Scandinavia pattern and a positive correlation with the North Atlantic Oscillation (0.31 ± 0.22) and Arctic Oscillation (0.42 ± 0.20). The meridional pattern is associated with more dominant north-westerly and westerly winds driven by the Scandinavia pattern and North Atlantic Oscillation, respectively. All three climatic indices show a statistically significant time-variable correlation with Baltic Sea wave heights during the winter season. When the Scandinavia pattern’s influence is strong, the North Atlantic and Arctic Oscillation effects are low and vice versa. The results are backed up by simulations using synthetic data that demonstrate that the percentage of variance explained using EOF analysis from the satellite-derived wave measurements is directly related to the percentage of noise in the data and that the retrieved spatial patterns are insensitive to the level of noise.

Observed Trends and Variability of Temperature and Precipitation and Their Global Teleconnections in the Upper Indus Basin, Hindukush-Karakoram-Himalaya

Having an extreme topography and heterogeneous climate, the Upper Indus Basin (UIB) is more likely to be affected by climate change and it is a crucial area for climatological studies. Based on the monthly minimum temperature (Tmin), maximum temperature (Tmax) and precipitation from nine meteorological stations, the spatiotemporal variability of temperature and precipitation were analyzed on monthly, seasonal, and annual scales. Results show a widespread significant increasing trend of 0.14 °C/decade for Tmax, but a significant decreasing trend of −0.08 °C/decade for Tmin annually, during 1955–2016 for the UIB. Seasonally, warming in Tmax is stronger in winter and spring, while the cooling in Tmin is greater in summer and autumn. Results of seasonal Tmax indicate increasing trends in winter, spring and autumn at rates of 0.38, 0.35 and 0.05 °C/decade, respectively, while decreasing in summer with −0.14 °C/decade. Moreover, seasonal Tmin results indicate increasing trends in winter and spring at rates of 0.09 and 0.08 °C/decade, respectively, while decreasing significantly in summer and autumn at rates of −0.21 and −0.22 °C/decade respectively for the whole the UIB. Precipitation exhibits an increasing trend of 2.74 mm/decade annually, while, increasing in winter, summer and autumn at rates of 1.18, 2.06 and 0.62 mm/decade respectively. The warming in Tmax and an increase in precipitation have been more distinct since the mid-1990s, while the cooling in Tmin is observed in the UIB since the mid-1980s. Warming in the middle and higher altitude (1500–2800 m and >2800 m) are much stronger, and the increase is more obvious in regions with elevation >2800 m. The wavelet analysis illustrated sporadic inter-annual covariance of seasonal Tmax, Tmin and precipitation with ENSO, NAO, IOD and PDO in the UIB. The periodicities were usually constant over short timescales and discontinuous over longer timescales. This study offers a better understanding of the local climate characteristics and provides a scientific basis for government policymakers.

Spatial and Temporal Characteristics of Rainfall Anomalies in 1961–2010 in the Yangtze River Basin, China

Understanding rainfall anomalies and their relationship with floods in the Yangtze River Basin (YRB) is essential for evaluating flood disasters, which have a great impact on the development of agriculture and the economy. On the basis of daily rainfall data from 1961 to 2010 from 178 meteorological stations, the temporal and spatial characteristics of rainfall anomalies in the YRB were studied on an annual scale, seasonal scale, and monthly scale. The annual rainfall of the YRB showed a generally increasing trend from 1961 to 2010 (14.22 mm/10 a). By means of the Bernaola–Galvan abrupt change test and Redfit spectrum analysis, it was found that the annual average rainfall increased abruptly after 1979 and had a cycle of 2–3 years. On the seasonal scale, the rainfall in spring and autumn showed a gradually decreasing trend, especially in September, while it showed a significant increasing trend in summer and winter in the YRB. As for the monthly scale, the rainfall in the rainy season from June to July presented a clear increasing trend during the study period, which greatly enhanced the probability of floods in the YRB. Additionally, through the analysis of the spatial distribution characteristics of rainfall in the entire YRB from 1961 to 2010, it was observed that the annual rainfall amount in the YRB presented an “increase–decrease–increase” tendency from east to west, accompanied by a rain belt that continuously moved from west to east. Moreover, the rainfall characteristics in flood years were summarized, and the results revealed that the years with rainfall anomalies were more likely to have flood disasters. However, anomalies alone would not result in big floods; the spatially and temporally inhomogeneous rainfall distribution might be the primary reason for flood disasters in the entire YRB.

Clarifying the propagation dynamics from meteorological to hydrological drought induced by climate change and direct human activities

AbstractAn understanding of the propagation process from meteorological to hydrological drought contributes to accurate prediction hydrological drought. However, the comprehensive influence of direct human activities involved in drought propagation is not well understood. In this study, an identification framework for drought propagation time was constructed to quantify the effects of direct human activities (i.e., reservoir storage, irrigation, industrial, domestic and agricultural water consumption) on drought propagation. Subsequently, the effects of meteorological and underlying surface factors on the drought propagation process were clarified based on random forest method, and the driving effect of teleconnection factors was investigated from top to bottom. The Wei River Basin (WRB), the largest tributary of the Yellow River Basin, was selected as the case study. Results disclosed that the propagation time from meteorological to hydrological drought was short in summer (approximately 2 months) and autumn (approximately 3 months), while long in spring (approximately 3–5 months) and winter (approximately 3–8 months), exhibiting noticeable spatial variability. In a changing environment, the propagation time generally showed a decreasing trend in spring and winter, while increasing propagation time was observed in summer and autumn. The dynamic drought propagation time of each season was all jointly controlled by the different extent variation of meteorological and underlying surface conditions, and the basic flow is all relatively significant throughout the period. Direct human activities had an effect on the seasonal dynamics of drought propagation, especially during the winter of the non-flood season, which alleviated the severity of winter hydrological drought to some extent, thus delaying the transmission of meteorological signals to hydrological systems. Sunspots, the dominant direct teleconnection driving force in the WRB, could indirectly affect the local precipitation and base flow in spring, autumn, and winter and interferes with the drought propagation process. This study sheds new insights into the attribution of drought propagation dynamics in a changing environment.

Absorbable aerosols based on OMI data: a case study in three provinces of Northeast China.

In order to assess the status of aerosol pollution in three selected Northeast Provinces of China, Ozone Monitoring Instrument/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13 × 24km V003 (OMAERUV) daily product data was used to evaluate (1) the ultraviolet aerosol index (UVAI) temporal and spatial distribution of the three Northeast Provinces from 2009 to 2018; (2) the potential pollution source areas of provincial capital cities; and (3) future trend changes. Furthermore, the influencing factors were also analyzed and are discussed herein. The results show that the UVAI in the Northeast Provinces exhibit an overall increasing trend, with an average annual increase rate of 2.99%. Seasonally, the UVAI increasing trend in winter is higher than in spring which in turn is higher than autumn. And summer has the least increasing trend. In addition, the external source of absorbent aerosol transmission is mainly in the southwest. Moreover, the overall UVAI remains relatively constant in the central part of the region, and increases slightly and significantly in the south and north directions. In general, spring, autumn, and winter all exhibit increasing trends in varying degrees. The difference between the forecasted and actual UVAI values in the Northeast Provinces does not exceed 10%; thus, the forecasting reliability is good. Also, UVAI has different degrees of correlation with natural factors, such as precipitation and temperature. With respect to social factors, UVAI and population density (a social factor) are positively correlated in 98.2% of the study area, demonstrating that there is a strong positive correlation between UVAI and smoke and dust emissions.

Precipitation efficiency of cloud and its influencing factors over the Tibetan plateau

AbstractThe basic characteristics of cloud water, precipitation, and the dependence of precipitation efficiency (PE) on the influencing factors over the Tibetan Plateau (TP) are investigated. Results found that the liquid water path shows a significant downward trend in winter over the TP, and the ice water path shows a significant upward trend in the pre‐monsoon and winter seasons and a significant downward trend in the monsoon season in the western TP from 1998 to 2015. In the eastern TP, the precipitation in the monsoon season also shows a significant downward trend, which may be related to the weakening of the South Asian monsoon. Results have determined that precipitation depends more on the ice water cloud than on the liquid water cloud over the TP. Moreover, the convective available potential energy (CAPE) and the low‐tropospheric relative humidity (RH) are two environmental factors that have a prominent influence on the PE. During the monsoon season, higher CAPE and RH were conducive to a larger PE over the TP. The results suggest that the CAPE has a positive effect on the PE, which means that the PE is directly dependent on the convective precipitation, mainly due to the frequent convective activity and dominant convective precipitation over the TP.

Variability of the precipitation over the Tianshan Mountains, Central Asia. Part I: Linear and nonlinear trends of the annual and seasonal precipitation

AbstractThe Tianshan Mountains, with their status as ‘water tower’, receive quantities of precipitation that are among the highest in Central Asia. There are considerable knowledge gaps regarding the understanding of spatial and temporal patterns of precipitation over this water‐scarce region. Based on the Global Precipitation Climatology Centre (GPCC) data set, this study evaluated the precipitation variations over Tianshan Mountains on different time scales by using Mann‐Kendall (M‐K) test approaches and the ensemble empirical mode decomposition (EEMD) method. The results show that (a) most parts of Tianshan experienced increasing annual precipitation during 1950–2016 while Western Tianshan, which is the wettest region, faced a downtrend of precipitation during the same 67 years; (b) the annual precipitation in the Tianshan Mountains has exhibited high‐frequency variations with 3‐ and 6‐year quasi‐periods and low‐frequency variations with 12‐, 27‐year quasi‐periods. On the decadal scale, Tianshan had two dry periods (1950–1962 and 1973–1984) and two wet periods (1962–1972 and 1985–2016) and has experienced a tendency of continuous humidification since 2004; (c) the precipitation over the Tianshan Mountains shows a strong seasonality. In total, 63.6% of all precipitation falls in spring and summer. Distinctive differences are found in seasonal precipitation variations among the sub‐Tianshan regions. Obvious upward trends of precipitation over Eastern Tianshan were found in all seasons, with Eastern Tianshan entering a humid period as early as 1986. Northern and Central Tianshan experienced a decreasing trend in summer and spring. However, in the other seasons, those two sub‐Tianshan regions have been in humid periods since the 1990s. The precipitation over Western Tianshan showed an upward trend in summer and autumn. The obvious downward trends in spring and winter have led to dry periods in these two seasons from 1997–2014 to 2008–2016, respectively.

Dynamic changes of vegetation coverage in China-Myanmar economic corridor over the past 20 years

The China-Myanmar Economic Corridor (CMEC) is a flagship project of the “Belt and Road” Initiative (BRI), which have made a major breakthrough from conceptual planning to actual construction in 2020, and subsequent construction activities will have a definite impact on local vegetation. To provide scientific support for vegetation conservation and sustainable development of the CMEC, statistical methods such as Morlet wavelet analysis, Mann-Kendall mutation test, Sen's slope estimator, Mann-Kendall trend test, and coefficient of variation were adopted to analyze the spatio-temporal changes in vegetation coverage; Hurst analysis was adopted to further predicted likely future development trends. The results suggested that: (1) The CMEC experienced an overall increasing Fractional Vegetation Cover (FVC) at a rate of 0.21%/yr from 2000 to 2019; 2005 was the mutation year when FVC changed from a slow increase to a significant increase. The FVC changes was mainly controlled by a 12-month oscillation period. The seasonal average FVC increase was slightly different, which were ranked in descending order, as winter (0.29%) > autumn (0.17%) > summer (0.14%) = spring (0.14%). The increasing trend in autumn and winter exceeded those in spring and summer, particularly after 2018. (2) The area with an increasing trend in FVC was five times of those with a decreasing trend (~49.40% VS ~ 9.97%). The former was mainly clustered in the Dehong Dai and Jingpo, China, central and southern part of sub-region Myanmar; whereas the latter primarily distributed in main urban zones such as Mangshi, Ruili, Mandalay, and Yangon. Above areas where FVC changes significantly were affected by human activities such as afforestation, agriculture and construction, and the fluctuation of FVC changes was strong in the short term. (3) Future changes in FVC indicated that ~ 88.08% of the CMEC will show a stable and positive trend, mainly agglomerated in forest and farmland zones. However, it is expected that vegetation coverage in main urban zones and several unused land zones formed by farmland degradation will experience further decrease, and the conservation of vegetation in these regions should be a focus during the construction of the CMEC.

Drivers of Twenty-First Century U.S. Winter Precipitation Trends in CMIP6 Models: A Storyline-Based Approach

AbstractClimate change during the twenty-first century has the potential to substantially alter geographic patterns of precipitation. However, regional precipitation changes can be very difficult to project, and in some regions, global climate models do not even agree on the sign of the precipitation trend. Since some of this uncertainty is due to internal variability rather than model bias, models cannot be used to narrow the possibilities to a single outcome, but they can usefully quantify the range of plausible outcomes and identify the combination of dynamical drivers that would be likely to produce each.This study uses a storylines approach—a type of regression-based analysis—to identify some of the key dynamical drivers that explain the variance in 21st century U.S. winter precipitation trends across CMIP6 models under the SSP3-7.0 emissions scenario. This analysis shows that the spread in precipitation trends is not primarily driven by differences in modeled climate sensitivity. Key drivers include global-mean surface temperature, but also tropical upper-troposphere temperature, the El Niño-Southern Oscillation (ENSO), the Pacific-North America (PNA) pattern, and the East Pacific (EP) dipole (a dipole pattern in geopotential heights over North America’s Pacific coast). Combinations of these drivers can reinforce or cancel to produce various high- or low-impact scenarios for winter precipitation trends in various regions of the United States. For example, the most extreme winter precipitation trends in the southwestern U.S. result from opposite trends in ENSO and EP, whereas the wettest winter precipitation trends in the midwestern U.S. result from a combination of strong global warming and a negative PNA trend.