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Normalized mutual information (NMI) is a nonparametric measure of the dependence between two variables without assumptions about the shape of their bivariate data distributions, but the implementation and interpretation of NMI in the coupled climate system is more complicated than for linear correlations. This study presents a joint approach combining correlation and NMI to examine land and ocean surface forcing of U.S. drought at varying lead times. Based on the distribution of correlation versus NMI between a source variable (local or remote forcing) and target variable [e.g., summer precipitation in the southern Great Plains (SGP)], newly proposed one-tail significance levels for NMI combined with two-tailed significance levels of correlation enable us to discern linearity and nonlinearity dominant regimes in a more intuitive way. Our analysis finds that NMI can detect strong linear relationships like correlations, but it is not exclusively tuned to linear relationships as correlations are. Also, NMI can further identify nonlinear relationships, particularly when there are clusters and blank areas (high density and low density) in joint probability distributions between source and target variables (e.g., detected between soil moisture conditions in eastern Montana from mid-February to mid-August and summer precipitation in the SGP). The linear and nonlinear information are found to be sometimes mixed and rather convoluted with time, for instance, in the subtropical Pacific of the Southern Hemisphere, revealing relationships that cannot be fully detected by either NMI or correlation alone. Therefore, this joint approach is a potentially powerful tool to reveal complex and heretofore undetected relationships. [ABSTRACT FROM AUTHOR]

California is one of the nation's top agriculture producers and is vulnerable to extreme events such as droughts and heat waves. Concurrent extreme events may further stress water and energy resources, exerting greater adverse socioeconomic, environmental, and health impacts than individual events. Here we examine the features of compound drought, heat wave, and dust events in California during spring and summer. From 2003 to 2020, 16 compound events are found in warm seasons, with a mean duration of ∼4 days. Compound events are characterized by enhanced surface temperature up to 4.5°C over northern and western California, reduced soil moisture and vegetation density, and an increase in dust optical depth (DOD) by 0.05–0.1 over central and southern California. The enhanced DOD is largely associated with severe vegetation dieback that favors dust emissions and southeasterly wind anomalies that support northward transport of dust from source regions in southern California. Surface fine dust and PM2.5 concentrations also increase by more than 0.5 and 5 μg m−3, respectively, during compound events associated with both enhanced dust emissions and a relatively stable atmosphere that traps pollutants. The development of the compound events is related to an anomalous high over the west coast in the lower to middle troposphere, which is a pattern favoring sinking motion and dry conditions in California. The anomalous high is embedded in a wave train that develops up to 7 days before the events. In comparison with heat wave extremes alone, compound events show significantly higher DOD and lower vegetation density associated with droughts. [ABSTRACT FROM AUTHOR]

Drought is a major natural hazard with far-reaching social, economic, and environmental impacts whose characteristics are highly interdependent across different spatial and temporal scales. Traditional global warming impact assessments on drought at the global scale have, however, taken into account only one drought characteristic at a time, likely leading to an underestimation of the overall impact. Here, we perform a trivariate analysis of changes in drought conditions at 1.5°, 2°, and 3°C global warming levels using 25 CMIP6 GCMs. Drought properties are characterized by the Standardized Soil Moisture Index (SSI). The future joint return periods of droughts historically associated with 10-, 20-, and 30-yr return periods are computed under the warming levels using copula functions considering drought duration, peak, and severity. Our comparative assessments of global warming impact on drought properties between univariate and trivariate analyses corroborate the substantial underestimation of the impact by the univariate analysis. The trivariate analysis shows that around 63%–91% of the global land will be subject to more recurrent droughts, while the percentage of the land reduces to 41%–56% for the univariate analysis. The difference between the univariate and trivariate analyses enlarges with global warming levels and the extremity of drought events. Based on the trivariate analysis, a 30-yr drought would become at least threefold more recurrent in 11%, 15%, and 20% of the global land at 1.5°, 2°, and 3°C warming levels, respectively, but the univariate analysis could not reach such large increases in drought conditions. [ABSTRACT FROM AUTHOR]

Diagnosis of rapidly developing springtime droughts in the central United States has mostly been made via numerous individual case studies rather than in an aggregate sense. This study investigates common aspects of subseasonal "meteorological drought" evolution, here defined as persistent precipitation minus evapotranspiration (P − ET) deficits, revealed in early (1 April–15 May) and late (16 May–30 June) spring composites of 5-day running mean JRA-55 reanalysis data for three different central U.S. regions during 1958–2018. On average, these droughts are initiated by a quasi-stationary Rossby wave packet (RWP), propagating from the western North Pacific, which arises about a week prior to drought onset. The RWP is related to a persistent ridge west of the incipient drought region and strong subsidence over it. This subsidence is associated with low-level divergent flow that dries the atmosphere and suppresses precipitation for roughly 1–2 weeks, and generally has a greater impact on the local moisture budget than does reduced poleward moisture transport. The resulting "dynamically driven" evaporative demand corresponds to a rapid drying of the root-zone soil moisture, which decreases around 40 percentiles within about 10 days. Anomalous near-surface warmth develops only after the P − ET deficit onset, as does anomalously low soil moisture that then lingers a month or more, especially in late spring. The horizontal scale of the RWPs, and of the related drought anomalies, decreases from early to late spring, consistent with the climatological change in the Pacific Rossby waveguide. Finally, while this composite analysis is based upon strong, persistent P − ET deficits, it still appears to capture much of the springtime development of "flash droughts" as well. [ABSTRACT FROM AUTHOR]

Drought is projected to become more severe and widespread as global warming continues in the twenty-first century, but hydroclimatic changes and their drivers are not well examined in the latest projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Here, precipitation (P), evapotranspiration (E), soil moisture (SM), and runoff (R) from 25 CMIP6 models, together with self-calibrated Palmer drought severity index with Penman–Monteith potential evapotranspiration (scPDSIpm), are analyzed to quantify hydroclimatic and drought changes in the twenty-first century and the underlying causes. Results confirm consistent drying in these hydroclimatic metrics across most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, and Australia, although the drying magnitude differs, with the drying being more severe and widespread in surface SM than in total SM. Global drought frequency based on surface SM and scPDSIpm increases by ∼25%–100% (50%–200%) under the SSP2-4.5 (SSP5-8.5) scenario in the twenty-first century together with large increases in drought duration and areas, which result from a decrease in the mean and flattening of the probability distribution functions of SM and scPDSIpm, while the R-based drought changes are relatively small. Changes in both P and E contribute to the SM change, whereas scPDSIpm decreases result from ubiquitous PET increases and P decreases over subtropical areas. The R changes are determined primarily by P changes, while the PET change explains most of the E increase. Intermodel spreads in surface SM and R changes are large, leading to large uncertainties in the drought projections. SIGNIFICANCE STATEMENT: Drought may become more severe and widespread under greenhouse gas (GHG)-induced global warming in the twenty-first century based on model projections. However, there are still large uncertainties in projected future drought changes, especially regarding the extent to which drought changes depend on drought indices and the future emissions scenarios analyzed. The latest projections from CMIP6 models reaffirm the widespread drying and increases in agricultural drought by up to 200% over most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, Southeast Asia, and Australia under moderate-to-high emissions scenarios in the twenty-first century, despite large uncertainties in individual projections partly due to internal variability. Ubiquitous increases in atmospheric demand for moisture under rising temperatures and precipitation decreases over many subtropical regions are the main driver of the projected drying and drought increases. [ABSTRACT FROM AUTHOR]

Persistent drought events that cause serious damage to the economy and environment are usually intensified by the feedback between the land surface and atmosphere. Therefore, reasonably modeling land–atmosphere coupling is critical for skillful prediction of persistent droughts. However, most high-resolution regional climate modeling has focused on the amplification effect of land–atmosphere coupling on local anticyclonic circulation anomalies, while less attention has been paid to the nonlocal influence through altering large-scale atmospheric circulation. Here we investigate how the antecedent land–atmosphere coupling over the area south of Lake Baikal (ASLB) influences the drought events occurring over its downstream region [i.e., Northeast China (NEC)] by using the Weather Research and Forecasting (WRF) Model and a linear baroclinic model (LBM). When the ASLB region is artificially forced to be wet in the WRF simulations during March–May, the surface sensible heating is weakened and results in a cooling anomaly in low level atmosphere during May–July. Consequently, the anticyclonic circulation anomalies over ASLB and NEC are weakened, and the severity of NEC drought during May–July cannot be captured due to the upstream wetting in March–May. In the LBM experiments, idealized atmospheric heating anomaly that mimics the diabatic heating associated with surface wetness is imposed over ASLB, and the quasi-steady response pattern of 500-hPa geopotential height to the upstream wetting is highly consistent with that in the WRF simulation. In addition, the lower-level heating instead of the upper-level cooling makes a major contribution to the high pressure anomaly over NEC. This study implies the critical role of modeling upstream land–atmosphere coupling in capturing downstream persistent droughts. [ABSTRACT FROM AUTHOR]

Rapid-onset droughts, known as flash droughts, can have devastating impacts on agriculture, water resources, and ecosystems. The ability to predict flash droughts in advance would greatly enhance our preparation for them and potentially mitigate their impacts. Here, we investigate the prediction skill of the extreme 2012 flash drought over the U.S. Great Plains at subseasonal lead times (3 weeks or more in advance) in global forecast systems participating in the Subseasonal Experiment (SubX). An additional comprehensive set of subseasonal hindcasts with NASA’s GEOS model, a SubX model with relatively high prediction skill, was performed to investigate the separate contributions of atmospheric and land initial conditions to flash drought prediction skill. The results show that the prediction skill of the SubX models is quite variable.While skillful predictions are restricted to within the first two forecast weeks in most models, skill is considerably better (3–4 weeks or more) for certain models and initialization dates. The enhanced prediction skill is found to originate from two robust sources: 1) accurate soil moisture initialization once dry soil conditions are established, and 2) the satisfactory representation of quasi-stationary cross-Pacific Rossby wave trains that lead to the rapid intensification of flash droughts. Evidence is provided that the importance of soil moisture initialization applies more generally to central U.S. summer flash droughts. Our results corroborate earlier findings that accurate soil moisture initialization is important for skillful subseasonal forecasts and highlight the need for additional research on the sources and predictability of drought-inducing quasi-stationary atmospheric circulation anomalies. [ABSTRACT FROM AUTHOR]

Northeast China (NEC) suffered a severe drought that persisted from March to July of 2017 with profound impacts on agriculture and society, raising an urgent need to understand the mechanism for persistent droughts over midlatitudes. Previous drought mechanism studies focused on either large-scale teleconnections or local land–atmosphere coupling, while less attention was paid to their synergistic effects on drought persistence. Here we show that the 2017 NEC drought was triggered by a strong positive phase of the Arctic Oscillation in March, and maintained by the anticyclone over the area south to Lake Baikal (ASLB) through a quasi-stationary Rossby wave in April–July, accompanied by sinking motion and north wind anomaly. By using a land–atmosphere coupling index based on the persistence of positive feedbacks between the boundary layer and land surface, we find that the coupling states over NEC and ASLB shifted from a wet coupling in March to a persistently strengthened dry coupling in April–July. Over ASLB, the dry coupling and sinking motion increased surface sensible heat, decreased cloud cover, and weakened longwave absorption, resulting in a diabatic heating anomaly in the lower atmosphere and a diabatic cooling anomaly in the upper atmosphere. This anomalous vertical heating profile led to a negative anomaly of potential vorticity at low levels, indicating that the land–atmosphere coupling had a phase-lock effect on the Rossby wave train originating from upstream areas, and therefore maintained the NEC drought over downstream regions. Our study suggests that an upstream quasi-stationary wave pattern strengthened by land–atmosphere coupling should be considered in diagnosing persistent droughts, especially over northern midlatitudes. [ABSTRACT FROM AUTHOR]

In the mid-twentieth century (1948–57), North America experienced a severe drought forced by cold tropical Pacific sea surface temperatures (SSTs). If these SSTs recurred, it would likely cause another drought, but in a world substantially warmer than the one in which the original event took place. We use a 20-member ensemble of the GISS climate model to investigate the drought impacts of a repetition of the mid-twentieth-century SST anomalies in a significantly warmer world. Using observed SSTs and mid-twentieth-century forcings (Hist-DRGHT), the ensemble reproduces the observed precipitation deficits during the cold season (October–March) across the Southwest, southern plains, and Mexico and during the warm season (April–September) in the southern plains and the Southeast. Under analogous SST forcing and enhanced warming (Fut-DRGHT, ≈3 K above preindustrial), cold season precipitation deficits are ameliorated in the Southwest and southern plains and intensified in the Southeast, whereas during the warm season precipitation deficits are enhanced across North America. This occurs primarily from greenhouse gas–forced trends in mean precipitation, rather than changes in SST teleconnections. Cold season runoff deficits in Fut-DRGHT are significantly amplified over the Southeast, but otherwise similar to Hist-DRGHT over the Southwest and southern plains. In the warm season, however, runoff and soil moisture deficits during Fut-DRGHT are significantly amplified across the southern United States, a consequence of enhanced precipitation deficits and increased evaporative losses due to warming. Our study highlights how internal variability and greenhouse gas–forced trends in hydroclimate are likely to interact over North America, including how changes in both precipitation and evaporative demand will affect future drought. [ABSTRACT FROM AUTHOR]

Soil moisture anomalies within the root zone (roughly, soil depths down to ~0.4 m) typically persist only a few months. Consequently, land surface–related climate predictability research has often focused on subseasonal to seasonal time scales. However, in this study of multidecadal in situ datasets and land data assimilation products, we find that root zone soil moisture anomalies can recur several or more seasons after they were initiated, indicating potential interannual predictability. Lead–lag correlations show that this recurrence often happens during one fixed season and also seems related to the greater memory of soil moisture anomalies within the layer beneath the root zone, with memory on the order of several months to over a year. That is, in some seasons, notably spring and summer when the vertical soil water potential gradient reverses sign throughout much of North America, deeper soil moisture anomalies appear to return to the surface, thereby restoring an earlier root zone anomaly that had decayed. We call this process "reemergence," in analogy with a similar seasonally varying process (with different underlying physics) providing winter-to-winter memory to the extratropical ocean surface layer. Pronounced spatial and seasonal dependence of soil moisture reemergence is found that is frequently, but not always, robust across datasets. Also, some of its aspects appear sensitive to spatial and temporal sampling, especially within the shorter available in situ datasets, and to precipitation variability. Like its namesake, soil moisture reemergence may enhance interannual-to-decadal variability, notably of droughts. Its detailed physics and role within the climate system, however, remain to be understood. [ABSTRACT FROM AUTHOR]

In July-August (JA) of 2016, northeastern China (NEC) suffered from the most severe hot drought event of the past 50 years, leading to profound impacts on agriculture, the ecosystem, and society. Results indicate that the loss of sea ice over the Barents Sea (SICBS) in March might have influenced the hot drought events over NEC in JA for the period of 1997-2016. Further analyses reveal that lower SICBS is closely related to thinner snow depth over western Eurasia (SDWEA) in April. The decline of SDWEA leads to drier soil from the Yangtze River valley to northern China during May-June, which is favorable for precipitation deficiency over NEC in JA. Besides, the loss of SICBS in March and decline of SDWEA in April are closely related to the polar-Eurasia teleconnection pattern and dry soil over NEC in JA, which provides favorable atmospheric circulation patterns for occurrences of hot droughts. The large ensemble simulations from the Community Earth System Model and the numerical experiments based on version 4 of the Community Atmosphere Model further confirmed their connections and the associated possible physical processes. Therefore, snow depth and soil moisture might serve as linkages between Barents Sea ice in March and hot droughts over NEC during JA, and the Barents Sea ice in March might be an important potential predictor for the summer hot droughts over NEC. [ABSTRACT FROM AUTHOR]

The impacts of sea surface temperature (SST) anomalies and anthropogenic greenhouse gases on the likelihood of extreme drought occurring in the central United States in the year 2012 were investigated using large-ensemble simulations from a global atmospheric climate model. Two sets of experiments were conducted. In the first, the simulated hydroclimate of 2012 was compared to a baseline period (1986-2014) to investigate the impact of SSTs. In the second, the hydroclimate in a world with 2012-level anthropogenic forcing was compared to five 'counterfactual' versions of a 2012 world under preindustrial forcing. SST anomalies in 2012 increased the simulated likelihood of an extreme summer precipitation deficit (e.g., the deficit with a 2% exceedance probability) by a factor of 5. The likelihood of an extreme summer soil moisture deficit increased by a similar amount, due in great part to a large spring soil moisture deficit carrying over into summer. An anthropogenic impact on precipitation was detectable in the simulations, doubling the likelihood of what would have been a rainfall deficit with a 2% exceedance probability under preindustrial-level forcings. Despite this reduction in rainfall, summer soil moisture during extreme drought was essentially unaffected by anthropogenic forcing because of 1) evapotranspiration declining roughly one-to-one with a decrease in precipitation due to severe water supply constraint and despite higher evaporative demand and 2) a decrease in stomatal conductance, and therefore a decrease in potential transpiration, with higher atmospheric CO2 concentrations. [ABSTRACT FROM AUTHOR]

The semiarid U.S. Great Plains is prone to severe droughts having major consequences for agricultural production, livestock health, and river navigation. The recent 2012 event was accompanied by record deficits in precipitation and high temperatures during the May-August growing season. Here the physics of Great Plains drought are explored by addressing how meteorological drivers induce soil moisture deficits during the growing season. Land surface model (LSM) simulations driven by daily observed meteorological forcing from 1950 to 2013 compare favorably with satellite-derived terrestrial water anomalies and reproduce key features found in the U.S. Drought Monitor. Results from simulations by two LSMs reveal that precipitation was directly responsible for between 72% and 80% of the soil moisture depletion during 2012, and likewise has accounted for the majority of Great Plains soil moisture variability since 1950. Energy balance considerations indicate that a large fraction of the growing season temperature variability is itself driven by precipitation, pointing toward an even larger net contribution of precipitation to soil moisture variability. To assess robustness across a larger sample of drought events, daily meteorological output from 1050 years of climate simulations, representative of conditions in 1979-2013, are used to drive two LSMs. Growing season droughts, and low soil moisture conditions especially, are confirmed to result principally from rainfall deficits. Antecedent meteorological and soil moisture conditions are shown to affect growing season soil moisture, but their effects are secondary to forcing by contemporaneous rainfall deficits. This understanding of the physics of growing season droughts is used to comment on plausible Great Plains soil moisture changes in a warmer world. [ABSTRACT FROM AUTHOR]

The current California drought has cast a heavy burden on statewide agriculture and water resources, further exacerbated by concurrent extreme high temperatures. Furthermore, industrial-era global radiative forcing brings into question the role of long-term climate change with regard to California drought. How has human-induced climate change affected California drought risk? Here, observations and model experimentation are applied to characterize this drought employing metrics that synthesize drought duration, cumulative precipitation deficit, and soil moisture depletion. The model simulations show that increases in radiative forcing since the late nineteenth century induce both increased annual precipitation and increased surface temperature over California, consistent with prior model studies and with observed long-term change. As a result, there is no material difference in the frequency of droughts defined using bivariate indicators of precipitation and near-surface (10 cm) soil moisture, because shallow soil moisture responds most sensitively to increased evaporation driven by warming, which compensates the increase in the precipitation. However, when using soil moisture within a deep root zone layer (1 m) as covariate, droughts become less frequent because deep soil moisture responds most sensitively to increased precipitation. The results illustrate the different land surface responses to anthropogenic forcing that are relevant for near-surface moisture exchange and for root zone moisture availability. The latter is especially relevant for agricultural impacts as the deep layer dictates moisture availability for plants, trees, and many crops. The results thus indicate that the net effect of climate change has made agricultural drought less likely and that the current severe impacts of drought on California's agriculture have not been substantially caused by long-term climate changes. [ABSTRACT FROM AUTHOR]

Potential biases in tree-ring reconstructed Palmer drought severity index (PDSI) are evaluated using Thornthwaite (TH), Penman-Monteith (PM), and self-calibrating Penman-Monteith (SC) PDSI in three diverse regions of the United States and tree-ring chronologies from the North American drought atlas (NADA). Minimal differences are found between the three PDSI reconstructions and all compare favorably to independently reconstructed Thornthwaite-based PDSI from the NADA. Reconstructions are bridged with model-derived PDSI_TH and PDSI_PM, which both closely track modeled soil moisture (near surface and full column) during the twentieth century. Differences between modeled moisture-balance metrics only emerge in twenty-first-century projections. These differences confirm the tendency of PDSI_TH to overestimate drying when temperatures exceed the range of the normalization interval; the more physical accounting of PDSI_PM compares well with modeled soil moisture in the projection interval. Remaining regional differences in the secular behavior of projected soil moisture and PDSI_PM are interpreted in terms of underlying physical processes and temporal sampling. Results demonstrate the continued utility of PDSI as a metric of surface moisture balance while additionally providing two recommendations for future work: 1) PDSI_PM (or similar moisture-balance metrics) compare well to modeled soil moisture and are an appropriate means of representing soil-moisture balance in model simulations and 2) although PDSI_PM is more physically appropriate than PDSI_TH, the latter metric does not bias tree-ring reconstructions of past hydroclimate variability and, as such, reconstructions targeting PDSI_TH can be used with confidence in data-model comparisons. These recommendations and the collective results of this study thus provide a framework for comparing hydroclimate variability within paleoclimatic, observational, and modeled data. [ABSTRACT FROM AUTHOR]

This work discusses the land surface-atmosphere interactions during the severe drought of 2008 in southern South America, which was among the most severe in the last 50 years in terms of both intensity and extent. Once precipitation returned to normal values, it took about two months for the soil moisture content and vegetation to recover. The land surface effects were examined by contrasting long-term simulations using a consistent set of satellite-derived annually varying land surface biophysical properties against simulations using the conventional land-cover types in the Weather Research and Forecasting Model-Noah land surface model (WRF-Noah). The new land-cover dataset is based on ecosystem functional properties that capture changes in vegetation status due to climate anomalies and land-use changes. The results show that the use of realistic information of vegetation states enhances the model performance, reducing the precipitation biases over the drought region and over areas of excessive precipitation. The precipitation bias reductions are attributed to the corresponding changes in greenness fraction, leaf area index, stomatal resistance, and surface roughness. The temperature simulation shows a generalized increase, which is attributable to a lower vegetation greenness and a doubling of the stomatal resistance that reduces the evapotranspiration rate. The increase of temperature has a beneficial effect toward the eastern part of the domain with a notable reduction of the bias, but not over the central region where the bias is increased. The overall results suggest that an improved representation of the surface processes may contribute to improving the predictive skill of the model system. [ABSTRACT FROM AUTHOR]