A global dataset of standardized moisture anomaly index incorporating snow dynamics from 1948 to 2010

Drought indices are hard to balance in terms of versatility (effectiveness for multiple types of drought), flexibility of timescales, and inclusivity (to what extent they include all physical processes). A lack of consistent source data increases the difficulty of quantifying drought. Here, we present a global monthly drought dataset from 1948 to 2010 based on a multitype and multiscalar drought index, the standardized moisture anomaly index incorporating snow dynamics (SZIsnow), driven by systematic fields from an advanced data assimilation system. The proposed SZIsnow dataset includes different physical water‒energy processes, especially snow processes. Our evaluation of the dataset demonstrates its ability to distinguish different types of drought across different timescales. Our assessment also indicates that the dataset adequately captures droughts across different spatial scales. The consideration of snow processes improved the capability of SZIsnow, and the improvement is particularly evident over snow-covered high-latitude (e.g., Arctic region) and high-altitude areas (e.g., Tibetan Plateau). We found that 59.66 % of Earth's land area exhibited a drying trend between 1948 and 2010, and the remaining 40.34 % exhibited a wetting trend. Our results also show that the SZIsnow dataset successfully captured the large-scale drought events that occurred across the world; there were 525 drought events with an area larger than 500,000 square kilometers globally during the study period, of which nearly 70 % had a duration longer than 6 months. Therefore, this new drought dataset is well suited to monitoring, assessing, and characterizing drought, and can serve as a valuable resource for future drought studies.

Tree-ring oxygen isotopes record a decrease in Amazon dry season rainfall over the past 40 years

Extant climate observations suggest the dry season over large parts of the Amazon Basin has become longer and drier over recent decades. However, such possible intensification of the Amazon dry season and its underlying causes are still a matter of debate. Here we used oxygen isotope ratios in tree rings (δ18OTR) from six floodplain trees from the western Amazon to assess changes in past climate. Our analysis shows that δ18OTR of these trees is negatively related to inter-annual variability of precipitation during the dry season over large parts of the Amazon Basin, consistent with a Rayleigh rainout model. Furthermore δ18OTR increases by approximately 2‰ over the last four decades (~ 1970–2014) providing evidence of an Amazon drying trend independent from satellite and in situ rainfall observations. Using a Rayleigh rainout framework, we estimate basin-wide dry season rainfall to have decreased by up to 30%. The δ18OTR record further suggests such drying trend may not be unprecedented over the past 80 years. Analysis of δ18OTR with sea surface temperatures indicates a strong role of a warming Tropical North Atlantic Ocean in driving this long-term increase in δ18OTR and decrease in dry season rainfall.

Detection, Attribution, and Future Response of Global Soil Moisture in Summer

Soil moisture variations and its relevant feedbacks (e.g., soil moisture–temperature and soil moisture–precipitation) have a crucial impact on the climate system. This study uses reanalysis and Coupled Model Intercomparison Project phase 6 simulations datasets to detect, attribute, and project soil moisture variations. The effect of anthropogenic forcings [greenhouse gases (GHG), anthropogenic aerosols (AA), and land use (LU) change] on soil moisture is much larger than that of the natural forcing. Soil moisture shows a drying trend at a global scale, which is mainly attributed to GHG forcing. The effects of external forcings vary with the regions significantly. Over eastern South America, GHG, AA, and natural forcings make soil dry, while LU forcing makes the soil wet. Over severely drying Europe, all the external forcings including GHG, AA, LU, and natural forcing exhibit drying effect. The optimal fingerprint method detection results show that some of GHG, AA, LU, and natural signals can be detected in soil moisture variations in some regions such as Europe. The soil will keep drying in all scenarios over most parts of the globe except Sahel and parts of mid-latitudes of Asia. With the increase of anthropogenic emissions, the variation of global soil moisture will be more extreme, especially in hotspots where the land–atmosphere coupling is intensive. The drying trend of soil moisture will be much larger on the surface than in middle and deep layers in the future, and this phenomenon will be more severe under the high-emission scenario. It may be affected by increased evaporation and the effect of carbon dioxide fertilization caused by global warming.

Natural variability vs forced signal in the 2015–2019 Central American drought

The recent multi-year 2015–2019 drought after a multi-decadal drying trend over Central America raises the question of whether anthropogenic climate change (ACC) played a role in exacerbating these events. While the occurrence of the 2015–2019 drought in Central America has been asserted to be associated with ACC, we lack an assessment of natural vs anthropogenic contributions. Here, we use five different large ensembles—including high-resolution ensembles (i.e., 0.5∘ horizontally)—to estimate the contribution of ACC to the probability of occurrence of the 2015–2019 event and the recent multi-decadal trend. The comparison of ensembles forced with natural and natural plus anthropogenic forcing suggests that the recent 40-year trend is likely associated with internal climate variability. However, the 2015–2019 rainfall deficit has been made more likely by ACC. The synthesis of the results from model ensembles supports the notion of a significant increase, by a factor of four, over the last century for the 2015–2019 meteorological drought to occur because of ACC. All the model results further suggest that, under intermediate and high emission scenarios, the likelihood of similar drought events will continue to increase substantially over the next decades.

Extending and understanding the South West Western Australian rainfall record using a snowfall reconstruction from Law Dome, East Antarctica

South West Western Australia (SWWA) has experienced a prolonged reduction in rainfall in recent decades, with associated reductions in regional water supply and residential and agricultural impacts. The cause of the reduction has been widely considered but remains unclear. The relatively short length of the instrumental record limits long-term investigation. A previous proxy-based study used a statistically negative correlation between SWWA rainfall and snowfall from the Dome Summit South (DSS) ice core drilling site, Law Dome, East Antarctica, and concluded that the anomaly of recent decades is unprecedented over the ∼ 750-year period of the study (1250–2004 CE). Here, we extend the snow accumulation record to cover the period from 22 BCE to 2015 CE and derive a rainfall reconstruction over this extended period. This extended record confirms that the recent anomaly is unique in the period since 1250 CE and unusual over the full ∼ 2000-year period, with just two other earlier droughts of similar duration and intensity. The reconstruction shows that SWWA rainfall started to decrease around 1971 CE. Ensembles of climate model simulations are used to investigate the potential roles of natural variability and external climate drivers in explaining changes in SWWA rainfall. We find that anthropogenic greenhouse gases are likely to have contributed towards the SWWA rainfall drying trend after 1971 CE. However, natural variability may also have played a role in determining the timing and magnitude of the reduction in rainfall.

Evaluation of Climate in CMIP6 Models over Two Third Pole Subregions with Contrasting Circulation Systems

Reliable simulations of historical and future climate are critical to assessing ecological and hydrological responses over the Third Pole (TP). In this study, we evaluate the historical and future temperature and precipitation simulations of 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in southeastern TP (SETP) and the upstream of the Amu Darya and Syr Darya (UAS) regions, two typical TP subregions dominated by the Indian summer monsoon system and westerlies, respectively. Comparison against station observations suggests that CMIP6 models generally capture the intra-annual variability and spatial pattern of historical climate over both subregions. However, the wetting and cold biases observed in CMIP5 still persist in CMIP6; annual temperature is underestimated by most models and annual precipitation is overestimated by all models. Multi-model average cold biases in SETP and UAS are 1.18°C and 0.32°C, respectively, and wet biases in SETP and UAS are 119% and 46%, respectively. We further analyze climate projections under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Both SETP and UAS subregions are projected to experience significant warming in 2015–2100, with warming trends 34%–42% and 40%–50% higher than the global trend, respectively. Model projections suggest that the warming trend will slow down under SSP1-2.6 and SSP2-4.5 but further intensify under SSP5-8.5 in 2050–2100. Monsoon-dominated SETP is projected to experience a significant wetting trend stronger than UAS over the entire future period, especially in summer (cf. winter in westerlies-dominated UAS). Concurrently, a significant drying trend in summer is found in UAS during 2050–2100 under SSP5-8.5, suggesting the intensified uneven distributions of seasonal precipitation based on projections.

Long-term decrease in Asian monsoon rainfall and abrupt climate change events over the past 6,700 years

Asian summer monsoon (ASM) variability and its long-term ecological and societal impacts extending back to Neolithic times are poorly understood due to a lack of high-resolution climate proxy data. Here, we present a precisely dated and well-calibrated tree-ring stable isotope chronology from the Tibetan Plateau with 1- to 5-y resolution that reflects high- to low-frequency ASM variability from 4680 BCE to 2011 CE. Superimposed on a persistent drying trend since the mid-Holocene, a rapid decrease in moisture availability between ∼2000 and ∼1500 BCE caused a dry hydroclimatic regime from ∼1675 to ∼1185 BCE, with mean precipitation estimated at 42 ± 4% and 5 ± 2% lower than during the mid-Holocene and the instrumental period, respectively. This second-millennium–BCE megadrought marks the mid-to late Holocene transition, during which regional forests declined and enhanced aeolian activity affected northern Chinese ecosystems. We argue that this abrupt aridification starting ∼2000 BCE contributed to the shift of Neolithic cultures in northern China and likely triggered human migration and societal transformation.

Holocene paleoenvironmental change inferred from two sediment cores collected in the Tibetan lake Taro Co

The Tibetan Plateau, also known as the “Water Tower of Asia” because of its function as a water storage and supply region, responds dramatically to modern climate changes. Paleoecological shifts inferred from lake sediment archives provide essential insights into past climate changes, and the processes that drove those shifts. This is especially true for studies of lakes in endorheic basins on the Tibetan Plateau, where lake level is regulated predominantly by Monsoon intensity. Such water bodies provide excellent opportunities to reconstruct past changes in humidity. Most paleolimnological investigations of lakes on the Tibetan Plateau, however, have involved the study of a single sediment core, making it difficult to discern between changes caused by local events and those caused by lake-wide or regional processes. Here we present results from a paleolimnological study of Lake Taro Co, a currently closed-basin lake in Central Tibet. We compared a sediment record from the central part of the lake to a record from the near-shore area, and present results of sedimentological and bioindicator (chironomid, diatom, pollen) analyses from both records. Results show three periods of lake-wide ecosystem change (> ca. 5250, 5250–2250 and < since about 2250 cal year BP), which reflect a continuous drying trend throughout the Middle and Late Holocene. In addition to this lake-wide trend, we identified two local events in the sediment core from the southeastern, nearshore site. These include (1) a hiatus between 12,400 and 5400 cal year BP and (2) an 1800-year period of distinct paleoenvironmental conditions (5400–3600 cal year BP). We hypothesize that both events were caused by relocation of a river in the southeast sector of the lake’s catchment. We propose that the first relocation caused an erosion event that removed sediment, thereby producing the hiatus. During the following 1800 years, the core site may have been located on the river delta, before another river relocation at 3600 cal year BP established the modern prodelta situation. Our study demonstrates the value of using multiple sediment cores from a lake, to better identify processes that control widespread versus local events.

Long-term trends of precipitation in Europe in different datasets

&lt;p&gt;It is already a well known fact that different types of climate datasets (station, gridded, reanalyses) and even individual datasets differ in how they describe statistical properties of climate variables. Here we compare precipitation trends in Europe between station data (taken from the ECA&amp;D database), gridded data (E-OBS and CRU TS), and reanalyses (JRA-55 and NCEP/NCAR) for period 1961-2011, both annually and for individual seasons. Theil-Sen non-parametric trend estimator is used for the quantification of the trend magnitude; Mann-Kendall test is used to evaluate the significance of trends.&lt;/p&gt;&lt;p&gt;On the annual basis, station data indicate precipitation increases in northern Europe and decreases in southern and southeastern Europe. Whereas trends in the gridded datasets roughly agree with station data, reanalyses provide much more negative trends with a different geographical distribution. There is a tendency for reanalyses to overestimate precipitation in the beginning of the period at some places, whereas they underestimate precipitation near the end of the period elsewhere. The disagreement among different data types and datasets is larger in all seasonal analyses except winter. Particularly notable is an excessive drying trend in central, southwestern, and southeastern Europe in NCEP/NCAR in most seasons. Reanalyses thus do not appear to be suitable data sources for estimation of precipitation trends. &amp;#160;&lt;/p&gt;&lt;p&gt;Reasons for the disagreement are varied and are conjectured by a detailed examination of station / point or regional time series: station series may suffer from inhomogeneities; gridded data may be affected by different sets of stations entering the interpolation procedure at different times; while reanalyses may be affected by different kinds of data being assimilated into them in different periods.&lt;/p&gt;