Spring Rainfall Research Articles

Long-Term Rainfall Trends in South West Asia—Saudi Arabia

In this study, rainfall data from 19 stations in Saudi Arabia (SA) for the period 1985-2019 was utilized to investigate interannual, monthly, and seasonal rainfall variations and trends. The magnitudes of these trends were characterized and tested using Mann-Kendall (MK) rank statistics at different significance levels. During this study period, the mean rainfall in SA showed a slight and significant decreasing trend by about 2 mm/35 years. Investigation of seasonal trends of rainfall revealed that Winter and Spring rainfall decreased significantly by 2.7 mm/35 years and 5.4 mm/35 years respectively. Three months showed very slight significant decreasing trends of rainfall. These were the months of February, March and April. Mann-Kendall analyses were carried out to investigate the annual trends of rainfall during three sub-periods, i.e., 1985-1996, 1997-2008, and 2009-2019. The results revealed that while rainfall increased by 5.3 mm/12 years and 7.8 mm/11 years for the first and the third periods respectively, it decreased by about 11 mm/12 years during the second period. While trends of rainfall in Saudi Arabia are affected by large scale circulations and local factors, the effect of extraterrestrial factors, such as solar activity and its consequent effects on the climate may, additionally, play a potential role in affecting the pattern of rainfall in Saudi Arabia.

Gain of one-month lead predicting spring rainfall over China: A comparison between FGOALS-f2 ensemble prediction system and its driving stretched-grid downscaling prediction system

Accurately one-month lead precipitation prediction is crucial for the regional disaster mitigation but challenging. Based on 20 years (2001−2020) hindcasts, this study compared the one-month lead prediction skills for precipitation in April between the Chinese Academy of Sciences Flexible Global Ocean-Atmosphere-Land System, Finite-Volume version 2 (FGOALS-f2) and its driving stretched-grid downscaling prediction system (the Unified global-to-regional prediction system, UGPS), to explore the gain of spring rainfall one-month lead prediction in stretched-grid downscaling prediction system. As a result, UGPS can significantly improve the prediction skill of rainfall for the total amount and extreme frequency in regional absolute amplitude compared with FGOALS-f2. The biases can be evidently reduced by 40%–98% for total rainfall and 76%–98% for extreme rainfall days and non-rainfall days over most of China. And the prediction skills for the interannual anomalies are slightly increased in UGPS but not as significant as the amplitude. The most remarkable improvement in UGPS against FGOALS-f2 is shown in the topographic areas with high altitudes (>2000 m) with a >40% bias reduction of predicted 20-year averaged total rainfall amount and a significant upgradation of prediction skill score for anomalous rainfall amplitude even though the score is still negative. This study suggests that the stretched-grid downscaling prediction system can improve the one-month lead prediction of intensity and extreme, but improving the interannual variability is still dependent on a better prediction from the “master” global climate model like FGOALS-f2.

Climate driven shifts in the synchrony of apple (Malus x domestica Borkh.) flowering and pollinating bee flight phenology

The phenology, or timing of key life-history events, of many globally important crops and the insects that pollinate them are shifting because of the changing climate. Where these temporal shifts occur at different rates or in different directions, it induces a risk of phenological mismatch, potentially reducing the quality and quantity of crop production. This study makes use of 48 years of UK citizen science (pollinating bee records) and systematic (apple flowering) data to report phenological shifts of apples and their bee-pollinator community. It quantifies the mismatches between peak flowering and flight dates which could potentially cause pollination deficits.Flowering onset and peak flowering dates of Bramley apples advanced throughout the study period. This advance was primarily driven by early spring temperatures, with peak flowering dates advancing by 6.7 ± 0.9 per 1 °C warming. In addition, increasing spring rainfall significantly delayed flowering dates by 0.4 ± 0.1 days per 10 mm additional rainfall. By contrast, bee phenology shifted in a non-linear manner, advancing from 1970 to 1985 before plateauing until the end of the study period. The peak flight date of the apple pollinating bee community appears to be similarly sensitive to spring temperatures, experiencing an advance of 6.5 ± 2.1 days per 1 °C warming, although individual bee species responses to climate varied.Furthermore, this study compared the phenological trends to assess the potential risk of asynchrony between crop and pollinator phenology. The different response patterns in the phenology of apples and bees led to shifting patterns of temporal mismatch between peak flowering and peak flight over time. Differences in sensitivity to climate do not appear to directly contribute to the phenological mismatch. Finally, this study highlights the potential value of citizen science data (with sufficient quality control) in understanding phenological shifts and mismatches and highlights potentially increasing temporal mismatch between apple trees and their bee pollinators.

Sea Surface Temperature Impact on Diurnal Cycle and Seasonal Evolution of the Guinea Coast Rainfall in Boreal Spring and Summer

Abstract ERA5 reanalyses and observations of convective clouds and precipitation are used over the northern Gulf of Guinea between 7°W and 3°E to study the influence of ocean surface temperature and the land–sea temperature gradient on Guinea Coast rainfall (GCR) in boreal spring and summer. Seasonal composites are calculated around two dates indexing the onset (Tref) and demise (Tend) of the GCR. The Tref date corresponds to the emergence of the equatorial upwelling in boreal spring, which “pushes” the zonal precipitation belt northward against the Guinea coast. The Tend date characterizes the emergence of the coastal upwelling in July, which is known to coincide with the beginning of the “Little Dry Season” that lasts until September. Along the Guinea Coast, the diurnal cycle of the air–sea temperature gradient controls precipitation through the land–sea breeze, which explains why precipitation reaches its maximum around noon over the ocean, and in the late afternoon over the continent. The emergence of the Guinea Coast upwelling in July induces a weakening of southerlies on a seasonal scale, and a weaker land breeze on a diurnal scale. It induces a decrease in the convergence of humidity transport across the coast and in coastal oceanic precipitation. Therefore, the GCR is seasonally controlled by the latitude of the maximum tropospheric water vapor content and the annual cycle of the West African monsoon, but the ocean surface temperature is responsible for the abruptness of its onset via the intensification of the equatorial upwelling around the end of May, and possibly of its demise as well via the emergence of the coastal upwelling by early July.

Moving waters to mitigate hydropeaking: A case study from the Italian Alps

AbstractWe assessed the effect of a hydropeaking diversion mitigation measure that allows for additional hydropower production, which markedly reduced hydropeaking on a 10‐km stream reach in the north‐eastern Italian Alps. Hydropeaking, caused by a storage hydropower plant, affected the study reach from the 1920s to 2015, when a cascade of three small run‐of‐the‐river plants was installed to divert the hydropeaks from the plant outlet directly into the intake of the RoRs plants, and hydropeaking was released downstream the confluence with a major free‐flowing tributary. The flow regime in the mitigated reach shifted from a hydropeaking‐dominated to a baseflow‐dominated regime in winter, with flow variability represented only by snowmelt and rainfall in late spring and summer. The application of two recently proposed sets of hydropeaking indicators, the hydraulic analysis of the hydropeaking wave, together with the assessment of biotic changes, allowed quantifying the changes in ecohydraulic processes associated with hydropeaking mitigation. The flow regime in the mitigated reach changed to a residual flow type, with much less frequent residual hydropeaks; although an average two‐fold increase in downramping rates were recorded downstream the junction with the tributary, these changes did not represent an ecological concern. The functional composition of the macrobenthic communities shifted slightly in response to flow mitigation, but the taxonomic composition did not recover to conditions typical of more natural flow regimes. This was likely due to the reduced dilution of pollutants and resulting slight worsening in water quality. Conversely, the hyporheic communities showed an increase in diversity and abundance of interstitial taxa, especially in the sites most affected by hydropeaking. This effect was likely due to changes in the interstitial space availability, brought by a reduction of fine sediments clogging. Besides illustrating a feasible hydropeaking mitigation option for Alpine streams, our work suggests the importance of monitoring both benthic and hyporheic communities, together with the flow and sediment supply regimes, and physico‐chemical water quality parameters.

Recent cover crop adoption is associated with small maize and soybean yield losses in the United States.

Cover crops are gaining traction in many agricultural regions, partly driven by increased public subsidies and by private markets for ecosystem services. These payments are motivated by environmental benefits, including improved soil health, reduced erosion, and increased soil organic carbon. However, previous work based on experimental plots or crop modeling indicates cover crops may reduce crop yields. It remains unclear, though, how recent cover crop adoption has affected productivity in commercial agricultural systems. Here we perform the first large-scale, field-level analysis of observed yield impacts from cover cropping as implemented across the US Corn Belt. We use validated satellite data products at sub-field scales to analyze maize and soybean yield outcomes for over 90,000 fields in 2019-2020. Because we lack data on cover crop species or timing, we seek to quantify the yield impacts of cover cropping as currently practiced in aggregate. Using causal forests analysis, we estimate an average maize yield loss of 5.5% on fields where cover crops were used for 3 or more years, compared with fields that did not adopt cover cropping. Maize yield losses were larger on fields with better soil ratings, cooler mid-season temperatures, and lower spring rainfall. For soybeans, average yield losses were 3.5%, with larger impacts on fields with warmer June temperatures, lower spring and late-season rainfall, and, to a lesser extent, better soils. Estimated impacts are consistent with multiple mechanisms indicated by experimental and simulation-based studies, including the effects of cover crops on nitrogen dynamics, water consumption, and soil oxygen depletion. Our results suggest a need to improve cover crop management to reduce yield penalties, and a potential need to target subsidies based on likely yield impacts. Ultimately, avoiding substantial yield penalties is important for realizing widespread adoption and associated benefits for water quality, erosion, soil carbon, and greenhouse gas emissions.

Characterizing the climate-phenology-hydrology associations in a subtropical forested watershed, central Taiwan

Upstream forested watersheds supply critical ecosystem services through providing clean freshwater and maintaining stable hydrological conditions. Responses of vegetation phenology to climatic variations have vital implications for hydrological regimes that are region-specific, but the associations of climate-phenology-hydrology have rarely been examined especially in tropical/subtropical regions. In this study, we utilized 46-year (1975–2020) hydroclimate records in forested watershed at central Taiwan, and showed that precipitation and streamflow anomalies and incidences of meteorological and hydrological droughts are becoming prominent after 2001. We further investigated the effects of monthly temperature and precipitation on vegetation growth using monthly EVI (enhanced vegetation index) of a watershed derived from MODIS (Moderate Resolution Imaging Spectroradiometer), and explored the effects of seasonal precipitation on the variations of vegetation phenological and subsequent watershed streamflow between 2001 and 2020. The EVI and temperature showed a linear relationship without time-lag effect (R2 = 0.50, p < 0.001), whereas EVI and precipitation exhibited a log-linear relationship with 2-month lag (R2 = 0.40, p < 0.001), indicating the accumulation of rainfall during relatively dry period was crucial for vegetation growth. Structural equation modeling revealed that earlier start of growing season (SOS) caused by relatively high spring rainfall (February-March) led to longer growing season (LOS) and higher P-Q deficit (precipitation minus runoff) during the growing season. Nevertheless, the large amount of precipitation during growing season has no effect on the end of growing season (EOS), LOS and P-Q deficit. Neither EOS has influence on LOS and P-Q deficit. Understanding the vegetation responses to climatic variations is required for future hydrologic regime projections, especially under changing climate.

Impact of the initial stratospheric polar vortex state on East Asian spring rainfall prediction in seasonal forecast models

Impact of the initial stratospheric polar vortex state on East Asian spring rainfall prediction in seasonal forecast models

Comparative analysis of long-term precipitation trends and its implication in the Modjo catchment, central Ethiopia

Abstract Understanding trends and variability of precipitation is essential to improve water resources utilization as well as agricultural activities. This study aims to investigate the spatiotemporal trends and variability of rainfall in the Modjo watershed, central Ethiopia. The Mann-Kendall trend (M–K) test, innovative trend analysis (ITA) and Sen's slope estimator were used to determine temporal trends, while the inverse distance weighted interpolation technique was adopted to visualize the spatial trends in time series. The result showed that complex patterns of rainfall variability that range from 16 to 59%, 18 to 63%, and 50 to 90% for the annual, summer, and spring seasons, respectively was observed over the study watershed. The result also indicated that significant trend (p &amp;lt; 0.05) in annual rainfall was detected only in 28.6% and 42.9% of the stations under the M-K test and ITA method, respectively, which indicates relatively more significant trends are displayed by the ITA method than the M–K test. At the seasonal scale, positive trends have been more dominant in the summer season (Z &amp;gt; 0, SITA &amp;gt; 0), whereas negative trends (Z &amp;lt; 0, SITA &amp;lt; 0) were detected in the spring season. Comparatively, the ITA method is found to be robust and allows more detailed trend analysis results using graphical illustrations for extreme events. The study concludes that the increasing and decreasing trends in summer and spring rainfall patterns could have implications leading to an increase in extreme events and lower agricultural productivity, respectively. The result suggests the need for planning effective adaptation strategies at the regional and local scales.

More profound impact of CP ENSO on Australian spring rainfall in recent decades

Most of Australia was in severe drought from 2018 to early 2020. Here we link this drought to the Pacific and Indian Ocean sea surface temperature (SST) modes associated with Central Pacific (CP) El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Over the last 20 years, the occurrence frequency of CP El Niño has increased. This study extends the previous understanding of eastern Pacific (EP) El Niño-Australian rainfall teleconnections, exhibiting that CP El Niño can bring much broader and stronger rainfall deficiencies than EP El Niño during austral spring (September–November) over the northern Australia (NAU), central inland Australia and eastern Australia (EAU). The correlations between SST fields and rainfall in three Cluster regions divided by clustering analysis also confirm this, with rainfall variability in most of Australia except southern Australia (SAU) most significantly driven by CP ENSO. Also, we demonstrate that the CP El Niño affects rainfall in extratropical EAU via the Pacific-South American (PSA) pattern. While the influence of EP El Niño is only confined in tropical NAU because its PSA pattern sits far too east to convey its variability. With the development of ENSO diversity since 2000, the footprint of El Niño on Australian rainfall has become more complex.

North China Spring Rainfall and Its Linkage with SST and Atmospheric Circulation

Abstract Spring rainfall is important for agriculture and economics in North China (NC). Thus, there is an imperative need for accurate seasonal prediction of the spring precipitation. This study implements a novel rainfall framework to improve understanding of NC spring rainfall. The framework is built based on a three-cluster normal mixture model. Distribution parameters are sampled using Bayesian inference and a Markov chain Monte Carlo algorithm. The probability behaviors of light, moderate, and heavy rainfall events can be reflected by the three rainfall clusters, respectively. Analysis of 61-yr data indicates that moderate rainfall makes the largest contribution (67%) to the total rainfall amount. The moderate rainfall intensity is mainly influenced by the sea surface temperature anomaly (SSTA) in the previous season over the equatorial eastern Pacific, and rainfall frequency is influenced by geopotential height anomaly in the mid- to high latitudes in spring. It is also found that more extreme precipitation events can be observed in the spring following an eastern Pacific El Niño event in the previous autumn and winter. Based on these relationships, we develop a multiple linear regression model. Hindcasts for spring precipitation using the model indicates that its anomaly correlation is 0.48, significant at the 99% confidence level. The result suggests that the newly developed model can well predict spring rainfall amount in NC.

Alternation of the Atmospheric Teleconnections Associated with the Northeast China Spring Rainfall during a Recent 60-Year Period

Alternation of the Atmospheric Teleconnections Associated with the Northeast China Spring Rainfall during a Recent 60-Year Period

Blue and Green Water Footprint of Agro-Industrial Avocado Production in Central Mexico

Mexico is the world-leading avocado producer. The municipality of Uruapan in the Avocado Belt region in Central Mexico produces 153,000 tons a year, nearly 6.4% of Mexico’s total volume. We performed a green and blue water footprint (WF) analysis between 2012 to 2017 in this municipality, and compared the estimated WF volumes with water concessions for agriculture. Mean annual rainfall was 1757.0 mm in the study period, mean effective rainfall 877.2 mm, mean crop evapotranspiration 933.1 mm, and 312.5 mm of mean irrigation requirement. The mean WFtotal was 744.3 m3 ton−1, below the global mean WF for this crop (1086 m3 ton−1). WFtotal was 2.5 times higher in irrigated plantations (1071.4 m3 ton⁻1) than in rainfed plantations (417.1 m3 ton−1). The crop yield was slightly higher (3.8%) under irrigated (10.26 ton ha−1 year−1) than in rainfed plantations (9.88 ton ha−1 year−1). WF and its components varied between years. The lowest WFblue was in 2015 when atypical spring rainfall increased available water during the dry season. The irrigation of avocado plantations doubles water use with a slight yield increase in relation to rainfed plantations. Regarding WF volumes and water concessions, we found that agroindustrial avocado production consumes up to 120% of the surface and groundwater volumes granted to agriculture use in years with dry conditions. The results indicate that other water users are depleted of this resource, creating water stress and scarcity, and leading to water rights conflicts and social discomfort.

Efficacy of linear multiple regression and artificial neural network for long-term rainfall forecasting in Western Australia

Precipitation is one of the most intrinsic resources for manifold industrial activities all over Western Australia; consequently, immaculate rainfall prediction is indispensable for flood mitigation as well as water resources management. This study investigated the performance of artificial neural networks (ANN) and Linear multiple regression (LMR) analysis to forecast long-term seasonal spring rainfall in Western Australia, using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential climatic phenomena. The ANN was developed in the form of multilayer perceptron using Levenberg–Marquardt algorithm and subsequently LMR was used with statistical significance for future spring rainfall forecast. The total climatic dataset has been divided into calibration and testing phases to determine the efficacy of the developed models. Different statistical skill tests such as root mean square error (RMSE), mean absolute error (MAE), and Willmott index of agreement ‘d’ were used to assess the efficacy of LMR and ANN modelling. In general, LMR has lower MAE and RMSE values as compared to ANN for most of the stations during calibration and testing periods, whereas ANN models performed better than LMR models based on ‘d’ values. The overall statistical analysis paradigm suggests the efficacy of LMR over ANN models for rainfall forecasting using more climatic variables. As a result, the developed LMR model, incorporated with lagged global climate indices, will facilitate the adequate preparedness for the risks associated with potential droughts in the study region.

The Adaptation to Freezing Tolerance of Hydrated Lettuce Seeds: Effects of Regional Climate and of Seed Characteristics

BACKGROUND: With global warming, soil seed banks at high altitudes face dual challenges, excessive water absorption and thinner snow cover that increase underground temperature. A better understanding of freezing tolerance of hydrated seeds provides insights for conservation in natural soil seed banks. OBJECTIVE: To understand the adaptation mechanisms of seed freezing tolerance under various climates, in relation to cooling rate and seed size. MATERIALS AND METHODS: Twelve ecotypes of lettuce (Lactuca sativa) seeds were collected from different geographical locations around the world. Seeds were fully hydrated and tested for their freezing tolerance using programmed cooling methods. RESULTS: The size of seeds from different climate regions varied, and was correlated with the freezing tolerance of the hydrated seeds (P&lt; 0.05). Larger seeds showed poorer freezing tolerance. The local climates of maternal plants were also well correlated to seed freezing tolerance ( P&lt; 0.05), especially under slow cooling conditions. The seeds collected in regions with high spring rainfall exhibited greater freezing tolerance. CONCLUSION: Freezing tolerance of hydrated seeds is affected by the climate of maternal plants and by seed size. Our data revealed the existence of an adaptation mechanism of freezing tolerance among various ecotypes of lettuce seeds.

Dormant Season Vegetation Phenology and Eddy Fluxes in Native Tallgrass Prairies of the U.S. Southern Plains

Carbon dioxide (CO2) fluxes and evapotranspiration (ET) during the non-growing season can contribute significantly to the annual carbon and water budgets of agroecosystems. Comparative studies of vegetation phenology and the dynamics of CO2 fluxes and ET during the dormant season of native tallgrass prairies from different landscape positions under the same climatic regime are scarce. Thus, this study compared the dynamics of satellite-derived vegetation phenology (as captured by the enhanced vegetation index (EVI) and the normalized difference vegetation index (NDVI)) and eddy covariance (EC)-measured CO2 fluxes and ET in six differently managed native tallgrass prairie pastures during dormant seasons (November through March). During December–February, vegetation phenology (EVI and NDVI) and the dynamics of eddy fluxes were comparable across all pastures in most years. Large discrepancies in fluxes were observed during March (the time of the initiation of growth of dominant warm-season grasses) across years and pastures due to the influence of weather conditions and management practices. The results illustrated the interactive effects between prescribed spring burns and rainfall on vegetation phenology (i.e., positive and negative impacts of prescribed spring burns under non-drought and drought conditions, respectively). The EVI better tracked the phenology of tallgrass prairie during the dormant season than did NDVI. Similar EVI and NDVI values for the periods when flux magnitudes were different among pastures and years, most likely due to the satellite sensors’ inability to fully observe the presence of some cool-season C3 species under residues, necessitated a multi-level validation approach of using ground-truth observations of species composition, EC measurements, PhenoCam (digital) images, and finer-resolution satellite data to further validate the vegetation phenology derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) during dormant seasons. This study provides novel insights into the dynamics of vegetation phenology, CO2 fluxes, and ET of tallgrass prairie during the dormant season in the U.S. Southern Great Plains.

Inter-comparison of past and projected climatic trends in Puerto Rico: 1950–2100

Abstract Past and projected climatic trends in Puerto Rico in the period 1950–2100 are evaluated by detection of slope and fit in smoothed time series and by the mapping of local and regional trends using 5- to 50-km resolution products. New outcomes include second-order upward trends for evaporation and sea surface height. At a regional scale, Hadley Cell overturning is drying the mid-troposphere, inducing a northerly tendency for trade winds. The past rainfall trend (1950–2020) has increased ∼10% on the Atlantic-facing seaboard. Warming seas (+.02 °C/year) and rising vegetation fraction induce more evaporation that is deepening the moist boundary layer and sustaining thermal orographic precipitation over the island. Historical trends and model projections show a decrease in rainfall in spring and an increase in autumn, attributable to the retreat of the jet stream and the influence of transpiration, respectively. Outcomes reveal competition between small- and large-scale processes, and an island-wide water balance sustained by diurnal cycling. Adapting to the rising sea level makes pro-active coastal management a necessity. HIGHLIGHTS Past and future climate changes are similar. Dataset and model resolution of &amp;lt;50 km help to quantify climate change for small islands. New research suggests that second-order trends are replacing linear trends. Impacts due to sea level rise and coastal erosion require management.

Altitude shape genetic and phenotypic variations in growth curve parameters of Larix kaempferi

To study the effects of geoclimatic variables of provenances on growth phenotypes and selected plus provenances, over 3000 trees of 22-year-old Larix kaempferi were evaluated from trials established in two climate zones for provenance selection and to explore the influence of climate variables on provenance performance. The material was replicated plantings of 84 open pollinated families from six provenances distributed in the mountains of central Japan. Provenance variation was observed in most age groups and the heritability of growth traits showed large differences. The phenotypic maximum value of height and diameter were significantly positive with altitude, and mean annual precipitation being important factors. Diameter at breast height growth was significantly negative with altitude and spring rainfall. The Ina provenance of relatively high altitudes, was well adapted to a variety of climates. Altitude might be the driving force for phenotypic and genetic variations and local adaptation.

Interannual Variations of Rainfall in Late Spring over Southwest China and Associated Sea Surface Temperature and Atmospheric Circulation Anomalies

Based on rainfall data for the period of 1960–2018 from 382 stations in southwest China and multiple reanalysis datasets, interannual variation of rainfall in late spring over Southwest China and associated sea surface temperature and atmospheric circulation anomalies are examined. The first leading mode of late-spring rainfall anomalies displays a uniform-distribution pattern. The second leading mode shows a zonal dipole pattern. The leading mode is related to an atmospheric wave train over mid-high latitudes of Eurasia, with a center of action of atmospheric anomaly over Southwest China. The atmospheric anomalies over Southwest China modulate late-spring rainfall there via modulating vertical motion and water vapor transport. In addition, the leading mode of late-spring rainfall anomalies has a close relation with sea surface temperature anomalies (SSTA) in the central and eastern equatorial Pacific. SSTA in the central and eastern equatorial Pacific impacts late-spring rainfall anomalies over Southwest China via modulation of the tropical Walker and Hadley circulation. The second leading mode of late-spring rainfall variation over Southwest China is closely associated with SSTA in the tropical western Pacific and a mid-high latitude wave train. SSTA in the tropical western Pacific and the mid-high latitudes wave train together leads to out-of-phase variation of meridional wind anomalies between western and eastern parts of Southwest China, which further results in a zonal dipole rainfall anomaly over Southwest China.

Decadal Background for Active Extreme Drought Episodes in the Decade of 2010–19 over Southeastern Mainland Asia

AbstractSevere and extreme drought in southeastern mainland Asia (SEMA) worsened drastically in 2010–19, occurring more than twice as frequently as in the preceding decade. It is found that the spring rainfall has undergone a concordant positive-to-negative transition with the turning point at 2010, and can explain 43% of the overall regime shift toward exaggerated severely dry condition. Associated with the decadal precipitation change, the anomalous northeasterlies prevail over SEMA, resulting in weakened eastward moisture propagation from the Indian Ocean as well as enhanced divergence. Meanwhile, there is downward motion over SEMA. This circulation pattern is remotely forced by a teleconnection from the tropical western Indian Ocean (TWI) SST. TWI SST is negatively correlated with SEMA precipitation and highlights a regime shift around 2010, after which the TWI has persistent warm SST helping to maintain deficient SEMA precipitation. In terms of the physical mechanism, the heating in the TWI warms the troposphere aloft and emanates wedge-shaped Kelvin waves with their northeast flank traversing SEMA, where friction-driven northeasterly low-level wind and divergence emerge to block moisture penetration from the Indian Ocean. The low-level divergence is followed by descending motion in SEMA, suppressing convection and rainfall. Further, the simulated structure forced by TWI SST alone bears a close resemblance to the observed evidence, confirming the critical role of the TWI. Finally, it is shown that ENSO and its diversity have a modulating effect on SEMA precipitation as well as on the coupling between TWI SST and SEMA precipitation, during both the previous winter and the concurrent spring.Significance StatementIn the last decade, a sequence of extreme droughts has swept southeastern mainland Asia (SEMA), resulting in tremendous losses. Instead of examining individual extreme cases, this study aims to advance the understanding of how the active extreme drought episodes can be modulated by the decadal background and to reveal the underlying physical mechanisms. The results suggest that decadal change can explain 43% of the overall regime shift toward more extreme dry conditions, and that the sea surface temperature in the tropical west Indian Ocean has a profound impact. The knowledge obtained here has benefits for estimation of overall risks to extreme drought hazards and highlights the future work direction that skillful decadal prediction is crucial for robust planning in an uncertain climate.