Self-calibrating Palmer Drought Severity Index Research Articles

Exploring the impact of the recent global warming on extreme weather events in Central Asia using the counterfactual climate data ATTRICI v1.1

We study the impact of recent global warming on extreme climatic events in Central Asia (CA) for 1901-2019 by comparing the composite representation of the observational climate with a hypothetical counterfactual one that does not include the long-term global warming trend. The counterfactual climate data are produced based on a simple detrending approach, using the global mean temperature (GMT) as the independent variable and removing the long-term trends from the climate variables of the observational data. This trend elimination is independent of causality, and the day-to-day variability in the counterfactual climate remains preserved. The analysis done in the paper shows that the increase in frequency and magnitude of extreme temperature and precipitation events can be attributed to global warming. Specifically, the probability of experiencing a +7 K temperature anomaly event in CA increases by up to a factor of seven in some areas due to global warming. The analysis reveals a significant increase in heatwave occurrences in Central Asia, with the observational climate dataset GSWP3-W5E5 (later called also factual) showing more frequent and prolonged extreme heat events than hypothetical scenarios without global warming. This trend, evident in the disparity between factual and counterfactual data, underscores the critical impact of recent climatic changes on weather patterns, highlighting the urgent need for robust adaptation and mitigation strategies. Additionally, using the self-calibrated Palmer drought severity index (scPDSI), the sensitivity of dry and wet events to the coupled precipitation and temperature changes is analyzed. The areas under dry and wet conditions are enhanced under the observational climate compared to a counterfactual scenario, especially over the largest deserts in CA. The expansion of the dry regions aligns well with the pattern of desert development observed in CA in recent decades.

Effects of weather and climate on fluctuations of grain prices in southwestern Bohemia, 1725–1824 CE

Abstract. Grain prices in early modern Europe reflected the effects of weather and climate on crop yields and a complex array of societal and socio-economic factors. This study presents a newly developed series of grain prices for Sušice (southwestern Bohemia, Czech Republic) for the period 1725–1824 CE, based on various archival sources. It aims to analyse their relationships with weather and climate, represented by temperature, precipitation, and drought (self-calibrated Palmer Drought Severity Index, scPDSI) reconstructions, as well as particular weather extremes and anomalies reported in documentary evidence. Wheat, rye, barley, and oats series in Sušice showed high mutual correlations. The mean highest prices during the year typically occurred from May to July before the harvest, while prices usually declined afterwards. Wheat, rye, and barley prices were significantly negatively correlated with spring temperatures and positively correlated with scPDSI from winter to summer. This indicates that wetter winters, cooler and wetter springs, and wetter summers contributed to higher prices. The extremely high grain prices in the years 1746, 1771–1772, 1802–1806, and 1816–1817 were separately analysed with respect to weather and climate patterns and other socio-economic and political factors. The results obtained were discussed in relation to data uncertainty, factors influencing grain prices, and the broader European context.

Spatial Heterogeneity in the Response of Winter Wheat Yield to Meteorological Dryness/Wetness Variations in Henan Province, China

Knowledge of the responses of winter wheat yield to meteorological dryness/wetness variations is crucial for reducing yield losses in Henan province, China’s largest winter wheat production region, under the background of climate change. Data on climate, yield and atmospheric circulation indices were collected from 1987 to 2017, and monthly self-calibrating Palmer drought severity index (sc-PDSI) values were calculated during the winter wheat growing season. The main results were as follows: (1) Henan could be partitioned into four sub-regions, namely, western, central-western, central-northern and eastern regions, based on the evolution characteristics of the time series of winter wheat yield in 17 cities during the period of 1988–2017. Among them, winter wheat yield was high and stable in the central-northern and eastern regions, with a remarkable increasing trend (p < 0.05). (2) The sc-PDSI in February had significantly positive impacts on climate-driven winter wheat yield in the western and central-western regions (p < 0.05), while the sc-PDSI in December and the sc-PDSI in May had significantly negative impacts on climate-driven winter wheat yield in the central-northern and eastern regions, respectively (p < 0.05). (3) There were time-lag relationships between the sc-PDSI for a specific month and the atmospheric circulation indices in the four sub-regions. Furthermore, we constructed multifactorial models based on selected atmospheric circulation indices, and they had the ability to simulate the sc-PDSI for a specific month in the four sub-regions. These findings will provide scientific references for meteorological dryness/wetness monitoring and risk assessments of winter wheat production.

Dryland hydroclimatic response to large tropical volcanic eruptions during the last millennium

Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM10cm), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.

A comparative study of various drought indices at different timescales and over different record lengths in the arid area of northwest China.

Although many drought indices have been developed to monitor drought conditions, their applicability differs across climatic regions, which results in different characteristics of drought index assessments at different timescales and over different record lengths. Therefore, the applicability of precipitation-based and precipitation-evapotranspiration/temperature-based drought indices was examined in this study using the Generalized Extreme Value Index (GEVI), Homogeneity Index (HI) of precipitation and temperature, K index (K), precipitation anomaly percentage (Pa), Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), and China-Z Index (CZI) over different record lengths and at a timescale range of 1-24months. In addition, the results that were obtained using these indices were compared with the Self-Calibrating Palmer Drought Severity Index (scPDSI). The stability, accuracy, and consistency of the different drought indices were evaluated using precipitation and evapotranspiration/temperature data (1-24months) collected from different climatic regions in the arid area of northwest China in the 1961-2017 period. The results indicated that the Pa, CZI, K, and SPEI were more stable; the SPI, SPEI, and HI were more accurate; and the GEVI, SPI, HI, and SPEI were more consistent with the scPDSI. In addition, the results indicated that it is more appropriate to select a long record length (> 35 years) to monitor drought when sufficient data are available. However, defining constant drought classes may not be appropriate for all drought timescales. In fact, precipitation and evapotranspiration data from different timescales had different optimal distribution functions. The drought indices also demonstrated that they were applicable to a temperate arid area in the study region. In addition, the HI and SPEI better captured the precipitation and evapotranspiration/temperature characteristics, while the CZI, K, and Pa overestimated or underestimated the frequency of different drought classes at different timescales to some extent in the study region. The results of this study suggest that greater priority should be given to the precipitation-evapotranspiration-based indices. In addition, it is suggested to change the drought index class thresholds in future related studies on drought event recognition at different timescales to ensure more accurate drought monitoring.

Multiscale Spatiotemporal Dynamics of Drought within the Yellow River Basin (YRB): An Examination of Regional Variability and Trends

Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape of the Yellow River Basin (YRB) is imperative for enhancing regional drought management and fostering ecological conservation alongside high-quality development. This study utilizes meteorological drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) and the self-calibrating Palmer Drought Severity Index (scPDSI), for a detailed spatiotemporal analysis of drought conditions. It examines the effectiveness of these indices in the basin’s drought monitoring, offering a comprehensive insight into the area’s drought spatiotemporal dynamics. The findings demonstrate the following: (1) SPEI values exhibit distinct fluctuation patterns at varying temporal scales, with more pronounced fluctuations at shorter scales. Drought years identified via the 12-month SPEI time scale include 1965, 1966, 1969, 1972, 1986, 1997, 1999, 2001, and 2006. (2) A modified Mann–Kendall (MMK) trend test analysis of the scPDSI time series reveals a worrying trend of intensifying drought conditions within the basin. (3) Correlation analysis between SPEI and scPDSI across different time scales yields correlation coefficients of 0.35, 0.54, 0.69, 0.76, and 0.62, highlighting the most substantial correlation at an annual scale. Spatial correlation analysis conducted between SPEI and scPDSI across various scales reveals that, within diverse temporal ranges, the correlation peaks at a 12-month time scale, with subsequent prominence observed at 6 and 24 months. This observed pattern accentuates the applicability of scPDSI in the monitoring of medium- to long-term drought phenomena.

Radial growth responses of Larix gmelinii to drought events in dry and wet areas of northern temperate forests

Drought stress caused by global climate warming affects tree growth in both dry and wet areas. However, the differences in tree growth responses to drought in dry and wet areas are poorly understood. Here, we collected 93 tree cores to analyze the differences in the radial growth responses of larch (Larix gmelinii) under climate change and tree growth resilience under drought events in the Altai Mountains (dry area) and Changbai Mountains (wet area). The results showed that larch growth in the Altai Mountains was significantly positively correlated with the self-calibrating Palmer Drought Severity Index (sc-PDSI) in all months and precipitation in the previous growth season and May, whereas it was significantly (p < 0.05) negatively correlated with temperature in May and the previous June to August. In the Changbai Mountains, larch growth was significantly positively correlated with May maximum and mean temperature, and significantly positively and negatively correlated with precipitation in April and May，respectively (p < 0.05). The mean resistance (recovery) of larch growth to drought in wet areas were significantly stronger (weaker) than that in dry areas (p < 0.05). Moreover, strengthening the drought frequency led to a significant (p < 0.05) decline in larch resistance in dry areas. Therefore, warming-induced increases in drought stress will aggravate negative impacts on the radial growth of larch forests in temperate dry areas but not in wet areas in the future.

Aging Mongolian pine plantations face high risks of drought-induced growth decline: evidence from both individual tree and forest stand measurements

Discerning vulnerability differences among different aged trees to drought-driven growth decline or to mortality is critical to implement age-specific countermeasures for forest management in water-limited areas. An important species for afforestation in dry environments of northern China, Mongolian pine (Pinus sylvestris var. mongolica Litv.) has recently exhibited growth decline and dieback on many sites, particularly pronounced in old-growth plantations. However, changes in response to drought stress by this species with age as well as the underlying mechanisms are poorly understood. In this study, tree-ring data and remotely sensed vegetation data were combined to investigate variations in growth at individual tree and stand scales for young (9 − 13 years) and aging (35 − 52 years) plantations of Mongolian pine in a water-limited area of northern China. A recent decline in tree-ring width in the older plantation also had lower values in satellited-derived normalized difference vegetation indices and normalized difference water indices relative to the younger plantations. In addition, all measured growth-related metrics were strongly correlated with the self-calibrating Palmer drought severity index during the growing season in the older plantation. Sensitivity of growth to drought of the older plantation might be attributed to more severe hydraulic limitations, as reflected by their lower sapwood- and leaf-specific hydraulic conductivities. Our study presents a comprehensive view on changes of growth with age by integrating multiple methods and provides an explanation from the perspective of plant hydraulics for growth decline with age. The results indicate that old-growth Mongolian pine plantations in water-limited environments may face increased growth declines under the context of climate warming and drying.

Global Drought-Wetness Conditions Monitoring Based on Multi-Source Remote Sensing Data

Drought is a common hydrometeorological phenomenon and a pervasive global hazard. To monitor global drought-wetness conditions comprehensively and promptly, this research proposed a spatial distance drought index (SDDI) which was constructed by four drought variables based on multisource remote sensing (RS) data, including the normalized difference vegetation index (NDVI), land surface temperature (LST), soil moisture (SM), and precipitation (P), using the spatial distance model (SDM). The results showed that the consistent area of SDDI with the 1-month and 3-month standardized precipitation-evapotranspiration index (SPEI1 and SPEI3), and the self-calibrating Palmer drought severity index (scPSDI) accounted for 85.5%, 87.3%, and 85.1% of the global land surface area, respectively, indicating that the index can be used to monitor global drought-wetness conditions. Over the past two decades (2001–2020), a discernible spatial distribution pattern has emerged in global drought-wetness conditions. This pattern was characterized by the extreme drought mainly distributed deep within the continent, surrounded by expanding moderate drought, mild drought, and no drought areas. On the annual scale, the global drought-wetness conditions exhibited an upward trend, while on the seasonal and monthly scales, it fluctuated steadily within a certain cycle. Through this research, we found that the sensitive areas of drought-wetness conditions were mainly found on the east coast of Australia, the Indus Basin of the Indian Peninsula, the Victoria and Katanga Plateau areas of Africa, the Mississippi River Basin of North America, the eastern part of the Brazilian Plateau and the Pampas Plateau of South America.

Resilience and response: Unveiling the impacts of extreme droughts on forests through integrated dendrochronological and remote sensing analyses

Extreme droughts are anticipated to have detrimental impacts on forest ecosystems, especially in water-limited regions, due to the influence of climate change. However, considerable uncertainty remains regarding the patterns in species-specific responses to extreme droughts. Here, we conducted a study integrating dendrochronology and remote sensing methods to investigate the mosaic-distributed maple-oak (native) natural forests and poplar plantations (introduced) in the Horqin Sandy Land, Northeast China. We assessed the impacts of extreme droughts on tree performances by measuring interannual variations in radial growth and vegetation index. The results showed that precipitation and self-calibrated palmer drought severity index (scPDSI) are the major factors influencing tree-ring width index (RWI) and normalized difference vegetation index (NDVI). The severe droughts between 2000 and 2004 resulted in reduced RWI in the three studied tree species as well as led to NDVI reductions in both the maple-oak natural forests and the poplar plantations. The RWI reached the nadir during the 2000–2004 severe droughts and remained at low levels two years after the severe drought, creating a legacy effect. In contrast to the lack of significant correlation between RWI and scPDSI, NDVI exhibited a significant positive correlation with scPDSI indicating the greater sensitivity of canopy performance to droughts than radial growth. Furthermore, interspecific differences in RWI and NDVI responses were observed, with the fast-growing poplar species experiencing a more significant RWI decrease and more negative NDVI anomaly during severe droughts than native species, highlighting the species-specific trade-offs between drought resilience and growth rate. This study emphasizes the importance of combining tree-level radial growth with landscape-scale canopy remote sensing to understand forest resilience and response. Our study improves our understanding of forest responses to extreme drought and highlights species differences in climate responses, offering crucial insights for optimizing species selection in sustainable afforestation and forest management in water-limited regions under the influence of climate change.

Drought limits vegetation carbon sequestration by affecting photosynthetic capacity of semi-arid ecosystems on the Loess Plateau

Drought is the driver for ecosystem production in semi-arid areas. However, the response mechanism of ecosystem productivity to drought remains largely unknown. In particular, it is still unclear whether drought limits the production via photosynthetic capacity or phenological process. Herein, we assess the effects of maximum seasonal photosynthesis, growing season length, and climate on the annual gross primary productivity (GPP) in vegetation areas of the Loess Plateau using multi-source remote sensing and climate data from 2001 to 2021. We found that maximum seasonal photosynthesis rather than growing season length dominates annual GPP, with above 90 % of the study area showing significant and positive correlation. GPP and maximum seasonal photosynthesis were positively correlated with self-calibrating Palmer Drought Severity Index (scPDSI), standardized precipitation and evapotranspiration index (SPEI) in >95 % of the study area. Structural equation model demonstrated that both drought indices contributed to the annual GPP by promoting the maximum seasonal photosynthesis. Total annual precipitation had a positive and significant effect on two drought indices, whereas the effects of temperature and radiation were not significant. Evidence from wood formation data also confirmed that low precipitation inhibited long-term carbon sequestration by decreasing the maximum growth rate in forests. Our findings suggest that drought limits ecosystem carbon sequestration by inhibiting vegetation photosynthetic capacity rather than phenology, providing a support for assessing the future dynamics of the terrestrial carbon cycle and guiding landscape management in semi-arid ecosystems.

Drought-heatwave compound events are stronger in drylands

Climate change is exacerbating the occurrence of compound droughts and heatwaves (CDHWs), which pose a serious threat to human health and socio-economic development. Using daily maximum temperature (Tmax) and monthly self-calibrating Palmer drought severity index (sc-PDSI) dataset, the evolution patterns of CDHWs and compound wet-heatwave events, the dominant drivers and the relative contributions of droughts and heatwaves in the drylands and humid areas from 1961 to 2020 were compared and analyzed. The results show that the CDHWs are stronger in drylands than in humid areas, the growth rate of CDHWs in drylands was almost twice that of the humid areas, the CDHWs are greater than the multi-year average intensity of compound wet-heatwave events by up to 2.4 times. Moreover, CDHWs has increased significantly from the past period (1961–1990) to the recent warm period (1991–2020), and the heatwave threshold has increased by about 5 °C. In most drylands, the contribution of heatwaves to CDHWs dominates, whereas in humid areas, the droughts contribution to CDHWs does. The compounding effects of droughts and heatwaves may exacerbate the severity of CDHWs regionally and are most pronounced in drylands, taking into account optimal lags. The study findings could provide scientific and technological support to actively address global climate change risks.

Asthma incidence can be influenced by climate change in Italy: findings from the GEIRD study—a climatological and epidemiological assessment

An association between climatic conditions and asthma incidence has been widely assumed. However, it is unclear whether climatic variations have a fingerprint on asthma dynamics over long time intervals. The aim of this study is to detect a possible correlation of the Summer North Atlantic Oscillation (S-NAO) index and the self-calibrated palmer drought severity index (scPDSI) with asthma incidence over the period from 1957 to 2006 in Italy. To this aim, an analysis of non-stationary and non-linear signals was performed on the time series of the Italian databases on respiratory health (ISAYA and GEIRD) including 36,255 individuals overall, S-NAO, and scPDSI indices to search for characteristic periodicities. The ISAYA (Italian Study on Asthma in Young Adults) and GEIRD (Gene Environment Interactions in Respiratory Diseases) studies collected information on respiratory health in general population samples, born between 1925 and 1989 and aged 20–84 years at the time of the interview, from 13 Italian centres. We found that annual asthma total incidence shared the same periodicity throughout the 1957–2006 time interval. Asthma incidence turned out to be correlated with the dynamics of the scPDSI, modulated by the S-NAO, sharing the same averaged 6 year-periodicity. Since climate patterns appear to influence asthma incidence, future studies aimed at elucidating the complex relationships between climate and asthma incidence are warranted.

Drought reconstruction since 1796 CE based on tree-ring widths in the upper Heilongjiang (Amur) River basin in Northeast Asia and its linkage to Pacific Ocean climate variability

Abstract. The economic and environmental impacts of persistent droughts in East Asia are of growing concern, and therefore it is important to study the cyclicity and causes of these regional droughts. The self-calibrating Palmer drought severity index (scPDSI) has been extensively employed to describe the severity of regional drought, and several scPDSI reconstructions based on tree rings have been produced. We compiled a tree-ring chronology for Hailar pine (Pinus sylvestris var. mongolica) from two sites in the Hailar region in the upper Heilongjiang (Amur) River basin. Analysis of the climate response revealed that scPDSI was the primary factor limiting tree ring growth from May to July. The mean May to July scPDSI in the Hailar region since 1796 was reconstructed from the tree-ring width chronology. The results of spatial correlation analysis revealed that the reconstructed scPDSI in this region responded significantly to climate change. Analysis of the synoptic climatology indicated that the drought in the upper Heilongjiang (Amur) River basin is closely related to El Niño–Southern Oscillation (ENSO) and the Silk Road teleconnection. The results of atmospheric water cycle analysis show that water vapor transport processes are the dominant factor in the development of drought in this region.

Drought Forecasting Using Integrated Variational Mode Decomposition and Extreme Gradient Boosting

The current study seeks to conduct time series forecasting of droughts by means of the state-of-the-art XGBoost algorithm. To explore the drought variability in one of the semi-arid regions of Turkey, i.e., Denizli, the self-calibrated Palmer Drought Severity Index (sc-PDSI) values were used and projections were made for different horizons, including short-term (1-month: t + 1), mid-term (3-months: t + 3 and 6-months: t + 6), and long-term (12-months: t + 12) periods. The original sc-PDSI time series was subjected to the partial autocorrelation function to identify the input configurations and, accordingly, one- (t − 1) and two-month (t − 2) lags were used to perform the forecast of the targeted outcomes. This research further incorporated the recently introduced variational mode decomposition (VMD) for signal processing into the predictive model to enhance the accuracy. The proposed model was not only benchmarked with the standalone XGBoost but also with the model generated by its hybridization with the discrete wavelet transform (DWT). The overall results revealed that the VMD-XGBoost model outperformed its counterparts in all lead-time forecasts with NSE values of 0.9778, 0.9405, 0.8476, and 0.6681 for t + 1, t + 3, t + 6, and t + 12, respectively. Transparency of the proposed hybrid model was further ensured by the Mann–Whitney U test, highlighting the results as statistically significant.

Evaluation of COSMIC-2 performance in detecting atmospheric boundary layer height and analysis of its variation

The atmospheric boundary layer (ABL) height (ABLH) is an essential index for climate and weather studies in the troposphere. Obtaining abundant and precise observations is crucial for modeling the top of the ABL. The radio occultation can provide observation data of Earth’s atmosphere with high vertical resolution and comprehensive spatial coverage, benefiting from its measurement mode. Thanks to the improved quality of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC)-2 lower atmosphere observations, its substantial amount and higher-quality atmospheric profile data are well suited for ABLH detection. Therefore, 1.4 million COSMIC-2 refractivity profiles from October 2019 to September 2020 were employed to determine the ABLH, and its retrieval performance is assessed using the official COSMIC-2 product (zbalmax) and radiosonde data. The retrieval results show that most of the effectively detected ABLH occultation events occur over the ocean. Comparing COSMIC-2 ABLH and zbalmax, consistent accuracy is found with a standard deviation of 0.22 km. Similar biases are observed each month. And the inversion accuracy in the Northern Hemisphere is higher than in the Southern Hemisphere. The ABLH derived from radiosonde data and COSMIC-2 has a high correlation coefficient of no less than 0.75. The better accuracy happened in the DJF (i.e. from December to February) for both comparisons with two datasets. Additionally, the distribution and seasonal variations were revealed by modeling verified COSMIC-2 ABLH. The fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate (ERA5) surface temperature and self-calibrated Palmer Drought Severity Index are used to analyze the impact of temperature and drought on ABLH. The results indicate that higher surface temperatures lead to a smaller ABLH, whereas drought at the surface leads to a larger ABLH. Therefore, the higher precision ABLH can be derived from COSMIC-2 after verification, and we can reveal its seasonal variation and influencing factors on this basis.

Experiments of the efficacy of tree ring blue intensity as a climate proxy in central and western China

Abstract. To investigate the potential value of tree ring blue intensity as a robust climate proxy in central and western China, four species from five sites were assessed. As well as latewood inverted blue intensity, we also examined earlywood blue intensity. To explore the sensitivity of using different extraction parameter settings using the software CooRecorder, seven percentile (P) variant settings for earlywood blue intensity and latewood inverted blue intensity were used, namely P50 : 50, P60 : 40, P70 : 30, P80 : 20, P85 : 15, P90 : 10, and P95 : 5. Age-dependent spline was used for all, and the positive trends were not retained. Correlation analysis was applied between the tree ring parameter chronologies and monthly/seasonal mean temperature, precipitation, and self-calibrated Palmer drought severity index variables. Linear regression was also used to further highlight the potential of developing climate reconstructions using these species. Only subtle differences were found between the different percentile extraction variants. As has been shown for many other Northern Hemisphere studies, latewood inverted blue intensity expresses a strong positive relationship with growing-season temperatures (the two southern sites explain almost 56 % of the temperature variance when combined). However, the low latitude of these sites shows an exciting potential for regions south of 30∘ N that are traditionally not targeted for temperature reconstructions. Earlywood blue intensity also shows good potential to reconstruct hydroclimate parameters in some humid areas.

Increasing vapor pressure deficit accelerates land drying

Increase Vapor Pressure Deficit (VPD) imposes higher atmospheric demand on land evaporation in the warming climate. However, it remains uncertain that how the increasing evaporative stress may enhance the global pattern of land drying. Here, we have used self-calibrating Palmer Drought Severity Index (scPDSI) based on outputs from 20 CMIP6 models to study the contribution of VPD, precipitation and other climatic factors to scPDSI changes globally. Global land drying and wetting are found to be regionally dependent, with statistically significant enhancement of drying and wetting under SSP2-4.5, SSP3-7.0 and SSP5-8.5 pathways (2015–2100) compared to the historical period (1961–2014). Increasing precipitation is the main reason of land wetting, while the land drying is initially associated with precipitation deficit, it is partly dominated by the increasing VPD over 20 ∼ 27% of the global land, where the estimated VPD contribution is nearly 6 times of that of precipitation under high forcing pathways. Elevated CO2 concentration is suggested to partly mitigate land drying by altering vegetation physiology; however, this mitigation is quantified to be limited. Our findings highlight the key role of VPD in accelerating global pattern of land drying and its increasing dominance in the warming climate.

Analysis of tsagaan lake sediment, valley of the gobi lakes, Mongolia, to determine past environmental changes and the effect of ongoing global warming

The arid region of Mongolia is sensitive to climate change. Understanding of climate variations in the past plays an important role in predicting further climate changes. In this study, we aim to investigate the relationship between the climatic factor and sedimentation history in the late Holocene. We analyzed the 18TS1 core sample (136 cm in length) from the Tsagaan lake in the Valley of the Gobi Lakes, Mongolia. The sediment core mainly consists of clay and silt sediments, occasionally interrupted by the sand-dominated layers. 210Pb dating method is applied and indicates that the upper 24 cm sediment spans the sedimentation history of the last 87 years. Along-core variations in sediment characteristics such as organic matter, carbonate, and amorphous silica abundance are indicative of the drought -inducing period based on the significant correlations between sediment characteristics and Self-calibrated Palmer Drought Severity Index. Moreover, the enrichment of carbonates is a great indicator of shallow lake conditions prior to the lake disappearance during the dry period. The chemical composition of sand-dominated units in the sediment core well agrees with that of sand sheets and sand dunes in the catchment. Modern expansion and migration of sand sheets are identified by aerial photo imagery. The insufficient sediment chronology is limiting our interpretation, though; the comparison with the other paleoclimate records helps the establishment of environmental changes in the last millennium.

Drought characteristics and their impacts on vegetation net primary productivity in the subtropical China

Drought is one of the main factors limiting forest productivity, and thus greatly affects the carbon sink capacity of forests. Here we first chose two drought indices including standardized precipitation evapotranspiration index (SPEI) and self-calibrating Palmer drought severity index (scPDSI) to reflect and analyze the spatiotemporal patterns of drought in the subtropical China. Then, the validated CASA (Carnegie-Amer-Stanford Approach) model was applied to estimate forest net primary productivity (NPP) and further quantify the contributions of drought events and their characteristics on forest NPP. The results showed that drought events during 2000–2015 have resulted in a mean decline of forest NPP of 7.2%. Moderate or severe drought events reduced NPP more significantly than extremely severe drought events. In addition, there was 1–2 years of lagging in the NPP responses to drought, and the lagging time varied with forest types. Our study suggests that forest managers and local governments should pay more attention to the places with moderate and severe drought events, and take measures to avoid NPP decline within the 2 years after drought. Our study also provides data support for further identifying the contribution of drought to ecosystem carbon fluxes in the subtropical China.