Soil Moisture Anomalies Research Articles

Evaluation of Retrospective National Water Model Soil Moisture and Streamflow for Drought‐Monitoring Applications

AbstractThe National Oceanic and Atmospheric Administration (NOAA)’s National Water Model (NWM) provides analyses and predictions of hydrologic variables relevant to drought monitoring and forecasts at fine time and space scales (hourly, 0.25–1 km). We present results exploring the potential for NWM soil moisture and streamflow analyses to inform operational drought monitoring. Both agricultural and hydrologic drought monitoring rely either explicitly or implicitly on an accurate representation of anomalous soil moisture values. Much of our analysis focuses on comparisons of soil moisture anomalies in the NWM to those from in‐situ observations. To establish benchmarks for NWM soil moisture skill, we also include other gridded data sets currently used to inform the US Drought Monitor, specifically those from the North American Land Data Assimilation System phase 2 (NLDAS‐2) land surface models. We then compare NWM streamflow low flows with ∼500 stream gauges from the United States Geological Survey (USGS) Hydro‐Climatic Data Network of undisturbed basins. The NWM soil moisture simulation’s skill parallels that from NLDAS‐2. The accuracy of drought condition identification from NWM streamflow exceeds that based on soil moisture as determined by Critical Success Index scores for extreme dry percentiles. Different meteorological forcings are used in the operational NWM cycles than those used in this retrospective analysis. This forcing disconnect, together with concerns about current‐generation land surface model soil moisture‐transport schemes, inhibit its current operational use for drought monitoring.

Development of a composite drought indicator for operational drought monitoring in the MENA region

This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies’ technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context.

Sensitivity of the Land–Atmosphere Coupling to Soil Moisture Anomalies during the Warm Season in China and its Surrounding Areas

Significant temporal and spatial variability in soil moisture (SM) is observed during the warm season in China and its surrounding regions. Because of the existence of two different evapotranspiration regimes, i.e., soil moisture-limited and energy-limited, averaging the land–atmosphere (L–A) coupling strength for all soil wetness scenarios may result in the loss of coupling signals. This study examines the daytime-only L–A interactions under different soil moisture conditions, by using two-legged metrics in the warm season from May to September 1981–2020, partitioning the interactions between SM and latent heat flux (SM–LH, the land leg) from the interactions between latent heat flux and the lifting condensation level (LH–LCL, the atmospheric leg). The statistical results reveal large regional differences in warm-season daytime L–A feedback in China and its surrounding areas. As the soil becomes wetter, the positive SM–LH coupling strength increases in arid regions (e.g., northwest China, Hetao, and the Great Indian Desert) and the positive feedback shifts to the negative one in semi-arid/semi-humid regions (northeast and northern China). The negative LH–LCL coupling is most pronounced in wet soil months in arid regions, while the opposite is true for the Tibetan Plateau. In terms of intraseasonal variation, the large variability of SM in north China, the Tibetan Plateau, and India due to the influence of the summer monsoon leads to the sign change in the land segment coupling index, comparing pre- and post-monsoon periods. To further examine the impact of SM anomalies on L–A coupling and to explore evapotranspiration regimes in the North China Plain, four sets of sensitivity experiments with different soil moisture levels over a period of 10 years were conducted. Under relatively dry soil conditions, evapotranspiration is dominated by the soil moisture-limited regime with positive L–A coupling, regardless of external moisture inflow. The critical soil moisture value separating a soil moisture-limited and an energy-limited regime lies between 0.24 m3/m3 and 0.29 m3/m3. Stronger positive feedback under negative soil moisture anomalies may increase the risk of drought in the North China Plain.

An Analysis of the Lagged Relationship between Anomalies of Precipitation and Soil Moisture and Its Potential Role in Agricultural Drought Early Warning

Abstract The standardized precipitation index (SPI) is the most commonly used index for detecting and characterizing meteorological droughts, and it is also extensively used as a proxy variable for soil moisture anomalies (SMA) for the purpose of monitoring agricultural drought in absence of long-term soil moisture observations. However, the potential capability of SPI to warn of the time-lagged soil water deficit—following the well-known “drought cascade” effect—is often overlooked in agricultural drought studies. In this research, a time-lagged correlation analysis is used to evaluate the relationship between the SMA dataset, generated as part of the Global Drought Observatory of the European Union’s Copernicus Emergency Management Service, and a set of SPIs derived from the ERA5 reanalysis produced by the European Centre for Medium-Range Weather Forecasts. The possibility to achieve an optimal agreement between SPI and SMA that also preserves the early warning skills of SPI is evaluated. The results suggest that if only the correlation between SPI and SMA is considered, the maximum agreement is usually obtained with a zero lead time (almost 80% of the cases), with SPI-3 representing the best option in about 40% of the grid cells at global scale. By also accounting for the benefits of a positive lead time, short accumulation periods tend to be favored, with SPI-1 being the optimal choice in about one-half of the cases, and 10–20 days of lead time in more than 90% of the grid cells is achieved without any significant reduction in either correlation or skill in drought extreme detection.

Intensive land restoration projects alter mechanisms underpinning spatiotemporal soil moisture variability at a catchment scale: A case study in China

Soil moisture (SM) is a critical factor for material circulation and energy exchange in Earth’s critical zone, but it is spatially and temporally variable. This study aimed to provide new insight into spatiotemporal SM variability and its associative controls in areas where land restoration projects have been implemented. Specifically, we compared environmental controls on spatiotemporal SM variability in deep soil layers (0–500 cm) of two paired catchments, one of which was treated by the Gully Land Consolidation (GLC) project and the other which was not, where the slopes of both catchments had initially been impacted by the Grain for Green (GFG) program. For this purpose, we used the empirical orthogonal function (EOF) to decompose spatial and temporal SM anomalies. Two dominant spatial and temporal EOF anomalies (EOF1 and EOF2) were obtained from six soil layers in both catchments, with an explained variance of 86%–97% and 32%–53%, respectively. These spatial anomalies that derived from spatial structures exhibited similar characteristics and controls in both catchments, while underlying temporal SM dynamic mechanisms differed. Temporal dynamics of the treated catchment were lower in the gully area (a relative flat region), while the opposite was true for the gully area (at a lower elevation) in the untreated catchment. The GLC and GFG programs both altered catchment scale temporal SM dynamic forcings. Results obtained from this study are helpful for understanding spatiotemporal SM variability with associated the hydrological processes in areas where the intensive land restoration projects have been implemented at a catchment scale.

Land and Atmosphere Precursors to Fuel Loading, Wildfire Ignition and Post‐Fire Recovery

AbstractLand surface‐atmosphere coupling and soil moisture memory are shown to combine into a distinct temporal pattern for wildfire incidents across the western United States. We investigate the dynamic interplay of observed soil moisture, vegetation water content, and atmospheric dryness in relation to fuel loading, fire ignition and post‐fire recovery. We find that positive soil moisture anomalies around 5 months before fire ignition increase biomass growth in the subsequent months, thereby shaping fire‐prone vegetation conditions. Then, concurrent decrease in soil moisture, vegetation dehydration, and atmospheric dryness collectively contribute to the occurrence of fire ignition events. This is followed by a rapid recovery in both soil and atmospheric moisture within several weeks after the fire incidents. Our findings provide insights into understanding of wildfire ignition dynamics, supporting fire modeling and enabling improved fire predictions, early warning systems, and mitigation strategies.

Soil moisture–temperature coupling over India through multi-scale observations

ABSTRACT Soil moisture–temperature coupling has been shown to affect the severity and occurrences of extreme temperature events like heatwaves and droughts. In this study, we quantify the soil moisture–temperature coupling over India at daily and climatological scales. Our results show maximum climatological coupling over north and central India during pre-monsoon months. The coupling strength is related to soil moisture content. Daily coupling is calculated for two heatwave events (2009 and 2015) to determine whether land–atmosphere coupling enhances the heatwave event. We observed strong soil moisture–temperature coupling during the 2009 heatwave, whereas weak coupling is observed in the 2015 heatwave. Our results suggest that soil moisture anomalies could enhance heat anomalies and temperature anomalies through the reduction in latent heat flux, leading to enhanced soil moisture–temperature coupling. Thus our study highlights the importance of soil moisture and associated coupling in understanding and predicting heatwave events.

Assessing the soil moisture-precipitation feedback in Australia: CYGNSS observations

Previous modelling and case studies highlight the impacts of antecedent soil moisture on precipitation, showing the connection between the anomalous land surface and atmospheric conditions. However, observational evidence is lacking, especially on daily timescales, primarily due to the difficulty in assessing the interaction between soil moisture and atmospheric variability and dataset quality. Using satellite retrievals, this study investigates the relationship between soil moisture and next-day precipitation in Australia. Analysing the 5 year soil moisture data from the Cyclone Global Navigation Satellite System, we find that soil moisture anomalies influence next-day precipitation probability where higher soil moisture is associated with a higher probability of precipitation, even allowing for precipitation persistence. We also find that this feedback is generally positive in northern Australia but slightly negative in the southern regions, suggesting regional dependence. Linkages between the persistence of dry/wet soil moisture days and the possibility of wildfires and floods are also discussed. These findings have direct implications for the management and predictions of extreme conditions.

Regime shift of the interannual linkage between NDVI in the Arctic vegetation biome and Arctic sea ice concentration

Vegetation in the Arctic ecosystem is of particular interest due to its role in global carbon budgets and its feedbacks to the climate system. The variability of summer Arctic Normalized Difference Vegetation Index (NDVI) show a sudden change in 2010/2011. To explore the possible reasons, climatic variables in the ERA5 dataset are used in this research for statistical analyses, and numerical experiments based on ECHAM5 are performed to verify the results of statistical analyses. It is found that the relationship between Arctic NDVI and sea ice concentration (SIC) in north of the Barents Sea in March was not significant before 2009 (1982–2009, P1), but become stronger and statistically significant after 2010 (2010–2021, P2). The reason and the underlying mechanisms are then investigated as follows. The summer temperature, moisture condition, and atmospheric circulation corresponding to summer NDVI in P1 and P2 are different. These summer climatic anomalies associated with decreased SIC in north of the Barents Sea in March are similar to those associated with summer NDVI in P2, which are more favorable for higher summer NDVI in P2, whereas they differ substantially in P1. In P2, the net energy flux at the surface in spring exhibits more significant anomalies, indicating stronger sea-ice-atmosphere interactions in P2. Therefore, in P2, the significant anomalous Rossby wave in spring can propagates eastwards from the Barents Sea and interacts with the atmospheric circulation in the NDVI region. In spring, the precipitation, snowmelt, and soil moisture anomalies associated with decreased SIC in March can persist to summer, which can affect summer NDVI through soil moisture–evaporation–temperature positive feedback. However, in P1, the weaker sea-ice-atmosphere interaction associated with insignificant circulation and soil moisture anomalies in spring, which resulting in insignificant climatic anomalies for NDVI in summer. Numerical experiments using the ECHAM5 verify the proposed physical mechanisms.

The Empirical Influence of Tibetan Plateau Spring Soil Moisture on South Asian Monsoon Onset: A Linear Diagnostic Perspective

Abstract The South Asian high (SAH) location and intensity are linked with the latent heating of the Tibetan Plateau (TP) and Yangtze River basin. The relationship between SAH variability and its impact on South Asian monsoon (SAM) onset is rarely linked with TP soil moisture. This study uses remotely sensed soil moisture and reanalysis products to quantify the relationship between the TP spring (April–June) soil moisture with SAH and SAM onset during 1988–2008. The results show that the TP spring soil moisture and monsoon onset indices are negatively correlated (R < −0.65), whereas the SAH exhibits a significant positive correlation (R ≥ 0.70) with TP soil moisture. The monsoon onset shows a difference of 20–25 days between the early- and late-onset composites. Significant positive (negative) soil moisture anomalies persist over the TP during the early (late) onset followed by positive (negative) LH (SH) anomalies during early (late)-onset composites. The TP thermal forcing exhibited positive anomalies during the early (late)-onset composites implying significant soil moisture control over the diabatic heating, which favors vertical ascent over the eastern plateau. Such a pattern leads to an earlier formation and movement of the SAH toward the Bay of Bengal (BOB) and southwestward of the TP. Before the early and late monsoon onset composites, the SAH pentad evolution drives the lower-tropospheric westerlies/easterlies toward continental SA. In the Indian Ocean the wind shear and transition from prevailing easterlies into westerlies during the pre-onset, onset, and post-onset pentad results in strong/weak ascent affecting the onset timing over the Arabian Sea and continental SA with less influence over the BOB monsoon onset. Significance Statement The Tibetan Plateau heating is one of the key drivers of the Asian monsoon precipitation in the surrounding regions, which has been previously studied in detail. This study explored the Tibetan Plateau spring soil moisture’s effect on South Asian monsoon onset timing. The monsoon onset timing is calculated using changes in wind direction, atmospheric temperature, and relative precipitation magnitude. Results found that the spring soil moisture substantially affects the TP thermal heating and the SA monsoon onset timing and highlights the physical processes leading to changes in the monsoon onset timing. The inclusion of soil moisture in estimating the monsoon onset timing can provide a tangible way of improving our understanding of the monsoon and associated water resources management practices.

Global hotspots in soil moisture-based drought trends

Decreasing soil moisture and increasing frequency and intensity of soil drought episodes are among the frequently discussed consequences of ongoing global climate change. To address this topic, a water balance model SoilClim forced by climate reanalysis ERA5-Land was applied on a global scale to analyze the spatiotemporal variability of changes in soil moisture anomalies. The results revealed that the soil relative available water (AWR) significantly decreased on 31.1% of global non-glaciated land and significantly increased on 5.3% of such global non-glaciated land in 1981–2021. Decreasing AWR trends were detected over all continents and were particularly pronounced in South America, which experienced significant drying on more than half of the continent. The main drought ‘hotspots’ were identified in equatorial Africa, a large part of South America, the Midwest United States, and in a belt extending from eastern Europe to eastern Asia. A seasonal analysis of region-specific patterns further suggested drying in Europe in summer but an absence of a drying trend in winter. These results were supported by an analysis of the area affected by percentile-based drought on individual continents, revealing statistically significant increasing trends of 5th- and 10th-percentile droughts on all continents except Australia at an annual scale. Nevertheless, summer and autumn drought frequency increases were also detected in Australia. The seasonal trends were the most rapid in South America and Europe (except in winter). The distributions of AWR values, evaluated by Z scores, shifted remarkably toward drier conditions during the 2001–2021 period, particularly in South America and Asia. These results underscore the alarming increase in soil drought on a global scale, highlighting the need for effective drought management strategies.

Regimes of Soil Moisture–Wet-Bulb Temperature Coupling with Relevance to Moist Heat Stress

Abstract Human heat stress depends jointly on atmospheric temperature and humidity. Wetter soils reduce temperature but also raise humidity, making the collective impact on heat stress unclear. To better understand these interactions, we use ERA5 to examine the coupling between daily average soil moisture and wet-bulb temperature (Tw) and its seasonal and diurnal cycle at global scale. We identify a global soil moisture–Tw coupling pattern with both widespread negative and positive correlations in contrast to the well-established cooling effect of wet soil on dry-bulb temperature. Regions showing positive correlations closely resemble previously identified land–atmosphere coupling hotspots where soil moisture effectively controls surface energy partition. Soil moisture–Tw coupling varies seasonally closely tied to monsoon development, and the positive coupling is slightly stronger and more widespread during nighttime. Local-scale analysis demonstrates a nonlinear structure of soil moisture–Tw coupling with stronger coupling under relatively dry soils. Hot days with high Tw values show wetter-than-normal soil, anomalous high latent and low sensible heat flux from a cooler surface, and a shallower boundary layer. This supports the hypothesis that wetter soil increases Tw by concentrating surface moist enthalpy flux within a shallower boundary layer and reducing free-troposphere-air entrainment. We identify areas of particular interest for future studies on the physical mechanisms of soil moisture–heat stress coupling. Our findings suggest that increasing soil moisture might amplify heat stress over large portions of the world including several densely populated areas. These results also raise questions about the effectiveness of evaporative cooling strategies in ameliorating urban heat stress. Significance Statement The purpose of this study is to provide a global picture of the relationship between soil moisture anomalies and a heat stress metric that includes the joint effects of temperature and humidity. This is important because a better understanding of this relationship will help improve the prediction of extreme heat stress events and inform strategies for ameliorating heat stress. We find a widespread positive correlation between soil moisture and heat stress, in contrast to studies relying on temperature alone. This raises the possibility that, over much of the world, and in the most populous regions, strategies like irrigation or “greening” that can reduce temperature might be ineffective or even harmful in reducing heat stress with humidity incorporated.

Arctic Sea Ice Loss Inducing Northwest Extension of Summer Precipitation over the Tibetan Plateau

Abstract Summer precipitation over the Tibetan Plateau (TP) has experienced obvious changes in recent decades, with significantly increased trends observed over the northern and western regions during 1961–2020. Results indicate that there are two pathways linking them to the reduced Arctic sea ice from late spring (April and May) to early summer (June and July). First, decreased sea ice in late spring favors wet and dry soil over the eastern Caspian Sea and northeastern TP by stimulating anomalous wavelike patterns and modulating snow melting. Furthermore, the soil moisture anomalies during late spring could maintain to July because of memory effects, strengthen the midlatitude Silk Road pattern, and contribute to the formation of a dipole mode around TP, characterized by a west cyclone and an east anticyclone. Second, through exciting an anomalous Rossby wave directly spreading from the Arctic to TP, a similar dipole pattern on 500-hPa geopotential height could be associated with the decline of sea ice in early summer. Consequently, enhanced southwesterly winds shown with the west cyclone cause more water vapor input to the western TP, while easterly anomalies along with the east anticyclone inhibit climatological westerly winds and prevent water vapor from outputting. This dipole pattern finally brings more moisture accumulated in the western and northern TP and increases the precipitation. This study links heterogeneous changes in summer precipitation over TP to Arctic sea ice changes and provides insights for further investigation into whether the TP could serve as a bridge connecting the Arctic and tropical climates.

Spring biomass burning in Indochina enhances summer Yangtze River Valley rainfall through land–atmosphere interactions

Indochina is one of the regions with the most severe biomass burning (BB) in the world, which produces enormous amounts of atmospheric aerosols, mostly in spring. Moreover, the spring soil moisture anomalies in Indochina have been found to have a significant influence on the summer rainfall in the Yangtze River Valley (YRV). It is still partially unclear how spring BB in Indochina influences the local and regional climate and land–atmosphere interactions. Here, we use regional model experiments and observational data to show that the radiative effect of BB aerosols in Indochina stabilizes the atmosphere and reduces local precipitation and soil moisture. The dry soil in Indochina persists from spring to summer, which warms the land surface and the atmosphere. As a result, the western Pacific subtropical high (WPSH) is stronger and extends westward from spring to summer. This leads to stronger moisture transport to and more precipitation in the YRV (increases of approximately 5% in July and 10% in August). Thus, the effect of BB aerosols on the YRV rainfall is similar to that of the Indochina dry soil anomaly. Additionally, the increase in the YRV summer rainfall caused by the Indochina spring dry soil anomaly is almost doubled when there are BB aerosols compared to that without BB aerosols, suggesting the importance of BB aerosols in regulating the regional land–atmosphere interactions.

Combined large-scale tropical and subtropical forcing on the severe 2019–2022 drought in South America

Changes in the frequency and magnitude of dry spells have been recorded over the past few decades due to an intensification of the global water cycle. A long-term soil drying trend resulting from a joint contribution of natural decadal variability in precipitation levels and increasing temperatures, predisposed central-east South America (CESA) to experience during 2019–2022 a period of outstanding soil desiccation. Flash droughts led to large areas (~100.000{{km}}^{2}) in CESA covered by record-breaking soil dryness. April 2020 witnessed the most severe conditions, when over 30% of the region experienced negative soil moisture anomalies larger than two standard deviations. Internal variability, particularly El Niño–Southern Oscillation, explained the dynamical forcing of this extreme drought. Large precipitation deficits and enhanced evaporation in CESA resulted from a coupled tropical and subtropical forcing associated to pronounced changes in the normal Walker and Hadley Cells’ circulation and to the establishment of a Rossby wave extending from west south Pacific towards South America. These findings highlight the intricate interplay between different mechanisms in the occurrence of climate extremes, stressing the need for an adequate representation of the dynamical processes associated with daily-to-multiyear timescales in climate models.

Impact of Agricultural Drought on Barley and Wheat Yield: A Comparative Case Study of Spain and Germany

Given the growing interest in drought impacts on crops, this work studied the impact of agricultural drought on wheat and barley during the period 2001–2020. The study was carried out in the Spanish regions of Castilla y León and Castilla–La Mancha, with approximate areas of 94,000 km2 and 79,000 km2, respectively, and in the German regions of Nordrhein-Westfalen, Niedersachsen and Bayern, with approximate areas of 34,000 km2, 48,000 km2 and 71,000 km2, respectively. These are the main cereal-growing regions of Spain and Germany. Soil moisture (SM) in the root zone was extracted from the LISFLOOD model database, and SM anomalies were used as the agricultural drought index. Gross primary productivity (GPP) and leaf area index (LAI) variables were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the month in which SM is most influential on these crop state variables was identified. Crop yields in Spain and Germany were obtained from the Spanish Ministry of Agriculture, Fisheries and Food and the German Federal Statistical Office, respectively. Agricultural drought years and their impact on cereal yields were determined on a regional scale using three approaches based on the critical month with different time periods. These approaches were the use of the critical month and the two (before or after) and the three months (before and after) around the critical month. Two different analyses were used to identify the critical month, depending on the different environmental conditions in each country. These two approaches consisted of a monthly correlation analysis between SM anomalies and cereal yield in Spain and a monthly trend analysis of SM anomalies in Germany. The results showed a dependence of crop variables on SM in spring months in both countries and in summer months in Germany. Differences were found depending on the environmental conditions. A considerable reduction in cereal yields was obtained in Spain which exceeded 30%. Similarly, a worrying sign was observed in Germany, with a positive agricultural drought trend and a yield reduction of almost 5% in cereal crops. In view of future forecasts of the negative impact of climate change on global food production, this study provides valuable information for water and agricultural management under climate change scenarios. Both in regions that are already threatened and in those that until recently were not affected, it is necessary to study adaptation measures to avoid aggravating the impact of agricultural drought on crops, which could improve water productivity and future food security.

Drought thresholds that impact vegetation reveal the divergent responses of vegetation growth to drought across China.

Identifying droughts and accurately evaluating drought impacts on vegetation growth are crucial to understanding the terrestrial carbon balance across China. However, few studies have identified the critical drought thresholds that impact China's vegetation growth, leading to large uncertainty in assessing the ecological consequences of droughts. In this study, we utilize gridded surface soil moisture data and satellite-observed normalized difference vegetation index (NDVI) to assess vegetation response to droughts in China during 2001-2018. Based on the nonlinear relationship between changing drought stress and the coincident anomalies of NDVI during the growing season, we derive the spatial patterns of satellite-based drought thresholds (T SM ) that impact vegetation growth in China via a framework for detecting drought thresholds combining the methods of feature extraction, coincidence analysis, and piecewise linear regression. The T SM values represent percentile-based drought threshold levels, with smaller T SM values corresponding to more negative anomalies of soil moisture. On average, T SM is at the 8.7th percentile and detectable in 64.4% of China's vegetated lands, with lower values in North China and Jianghan Plain and higher values in the Inner Mongolia Plateau. Furthermore, T SM for forests is commonly lower than that for grasslands. We also find that agricultural irrigation modifies the drought thresholds for croplands in the Sichuan Basin. For future projections, Earth System Models predict that more regions in China will face an increasing risk for ecological drought, and the Hexi Corridor-Hetao Plain and Shandong Peninsula will become hotspots of ecological drought. This study has important implications for accurately evaluating the impacts of drought on vegetation growth in China and provides a scientific reference for the effective ecomanagement of China's terrestrial ecosystems.

Assessment of isoprene and near-surface ozone sensitivities to water stress over the Euro-Mediterranean region

Abstract. Plants emit biogenic volatile organic compounds (BVOCs) in response to changes in environmental conditions (e.g. temperature, radiation, soil moisture). In the large family of BVOCs, isoprene is by far the strongest emitted compound and plays an important role in ozone chemistry, thus affecting both air quality and climate. In turn, climate change may alter isoprene emissions by increasing temperature as well as the occurrence and intensity of severe water stresses that alter plant functioning. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) provides different parameterizations to account for the impact of water stress on isoprene emissions, which essentially reduces emissions in response to the effect of soil moisture deficit on plant productivity. By applying the regional climate–chemistry model RegCM4chem coupled to the Community Land Model CLM4.5 and MEGAN2.1, we thus performed sensitivity simulations to assess the effects of water stress on isoprene emissions and near-surface ozone levels over the Euro-Mediterranean region and across the drier and wetter summers over the 1992–2016 period using two different parameterizations of the impact of water stress implemented in the MEGAN model. Over the Euro-Mediterranean region and across the simulated summers, water stress reduces isoprene emissions on average by nearly 6 %. However, during the warmest and driest selected summers (e.g. 2003, 2010, 2015) and over large isoprene-source areas (e.g. the Balkans), decreases in isoprene emissions range from −20 % to −60 % and co-occur with negative anomalies in precipitation, soil moisture and plant productivity. Sustained decreases in isoprene emissions also occur after prolonged or repeated dry anomalies, as observed for the summers of 2010 and 2012. Although the decrease in isoprene emissions due to water stress may be important, it only reduces near-surface ozone levels by a few percent due to a dominant VOC-limited regime over southern Europe and the Mediterranean Basin. Overall, over the selected analysis region, compared to the old MEGAN parameterization, the new one leads to localized and 25 %–50 % smaller decreases in isoprene emissions and 3 %–8 % smaller reductions in near-surface ozone levels.

Monitoring hydrological changes with satellite data: Spring thaw's effect on soil moisture and groundwater in seasonal Freezing-Thawing zones

Due to the dense vegetation coverage in mountainous areas and difficulties in field monitoring in mid-high-latitude freezing-thawing zones, satellite and remote sensing technologies can be used to monitor long-term global hydrological changes. This study uses multiple satellite data of snow water equivalent (SWE), soil moisture (SM), and groundwater storage anomaly (GWSA) to analyse their spatial–temporal changes in the seasonal freezing-thawing Tumen River Basin. Water transformation during the thawing period is determined through groundwater level fluctuations and correlation analysis methods; thus, the recharge effects of snowmelt and seasonally frozen soil thawing on soil moisture and groundwater are identified. The snow begins to melt in February, and snow water equivalent decreases gradually from upstream to downstream after reaching the peak. Furthermore, seasonally frozen soil melts gradually from March. Soil moisture downstream is higher than that in the upper and middle reaches. Additionally, the GWSA increases gradually in the thawing period, which is high in mountainous areas and low in plains. The Spearman correlation coefficient among ΔSWE, ΔSM, and ΔGWSA is more significant than 0.5 and dependent on altitude. With snow and frozen soil melting, vertical infiltration and meltwater percolation increase soil moisture and GWSA. This phenomenon is predominant at low altitudes (<600 m) and pore phreatic groundwater in the middle and lower reaches. However, snowmelt is the dominant factor in groundwater recharge at high-altitude upper reaches. For seasonal freezing-thawing zones, a close water transformation was observed between snow melting, soil water thawing, and groundwater in spring. Thus, the environmental and ecological impact of spring snowmelt and floods in freezing-thawing zones can be monitored using multi-source data.

Quantitative Analysis of the Uncertainty of Drought Process Simulation Based on Atmospheric–Hydrological Coupling in Different Climate Zones

Droughts can lead to drought disasters, which have become one of the main natural disasters affecting the development of social economies and ecological environments around the world. Timely and effective drought process simulation and prediction based on atmospheric–hydrological coupling is crucial for drought prevention and resistance. The initial condition (IC) is one source causing uncertainty in drought process simulation and prediction, and the impacts are different with drought duration, basin size and region. Therefore, a quantitative method that measures the uncertainty caused by ICs on the drought process simulation in different climate zones is proposed in this study. In this study, the VIC (Variable Infiltration Capacity) model at a resolution of 0.05°, which is proven as an ideal model to reflect drought processes, was used as the hydrological model to obtain soil moisture. By analyzing the Soil Moisture Anomaly Percentage Index (SMAPI) error characteristics that were simulated based on different ICs, an uncertainty index for drought process simulation was constructed in different climate zones. It was found that with the development of a drought process, the uncertainty converges, and it decreases to within 10% after a drought occurs for 5 to 6 months, while it is less than 5% in the particular basin in a humid region. In climate transition zones, both the uncertainty and its decrease rate are greater than those in humid regions. Climate characteristics, as well as soil types and vegetation types, are fundamental factors that cause differences in drought process simulation and uncertainty changes. The precipitation and temperature distribution more obviously vary spatially and temporally, a greater uncertainty is caused by ICs. This quantitative method reveals the impact of ICs on drought process simulation in different climate regions and provides a basis for the further improvement of drought simulation and prediction based on atmospheric–hydrological coupling.