Interannual Variability Of Precipitation Research Articles

K-Means and C4.5 Decision Tree Based Prediction of Long-Term Precipitation Variability in the Poyang Lake Basin, China

The machine learning algorithms application in atmospheric sciences along the Earth System Models has the potential of improving prediction, forecast, and reconstruction of missing data. In the current study, a combination of two machine learning techniques namely K-means, and decision tree (C4.5) algorithms, are used to separate observed precipitation into clusters and classified the associated large-scale circulation indices. Observed precipitation from the Chinese Meteorological Agency (CMA) during 1961–2016 for 83 stations in the Poyang Lake basin (PLB) is used. The results from K-Means clusters show two precipitation clusters splitting the PLB precipitation into a northern and southern cluster, with a silhouette coefficient ~0.5. The PLB precipitation leading cluster (C1) contains 48 stations accounting for 58% of the regional station density, while Cluster 2 (C2) covers 35, accounting for 42% of the stations. The interannual variability in precipitation exhibited significant differences for both clusters. The decision tree (C4.5) is employed to explore the large-scale atmospheric indices from National Climate Center (NCC) associated with each cluster during the preceding spring season as a predictor. The C1 precipitation was linked with the location and intensity of subtropical ridgeline position over Northern Africa, whereas the C2 precipitation was suggested to be associated with the Atlantic-European Polar Vortex Area Index. The precipitation anomalies further validated the results of both algorithms. The findings are in accordance with previous studies conducted globally and hence recommend the applications of machine learning techniques in atmospheric science on a sub-regional and sub-seasonal scale. Future studies should explore the dynamics of the K-Means, and C4.5 derived indicators for a better assessment on a regional scale. This research based on machine learning methods may bring a new solution to climate forecast.

Ethylene-regulated leaf lifespan explains divergent responses of plant productivity to warming among three hydrologically different growing seasons.

Leaf senescence is known to be regulated by the plant hormone ethylene, but how leaf lifespan responds to global environmental change and links to ecosystem-level responses remains largely unexplored. Here we investigated the effects of climate warming and nitrogen addition on plant functional traits, plant hormone ethylene and net primary production in a 13-year field experiment in a desert steppe. Across the last 3years of the experiment (2016-2018), plant productivity increased under warming only in 2016, when there was above normal precipitation, but consistently increased with nitrogen addition. Warming enhanced net photosynthesis, leaf nitrogen and ethylene production and reduced leaf lifespan in 2016 (a wet year), but not in 2017 (a drought year); the effect of warming in 2018 (a year with normal precipitation) was opposite to 2016, likely due to the below-normal precipitation in the mid-growing season in 2018. Nitrogen addition led to increases in leaf nitrogen, ethylene production and net photosynthesis, and declines in leaf lifespan in 2016 and 2018, but not in 2017. The ethylene-regulated lifespan was further evidenced by the addition of CoCl2 (an ethylene biosynthesis inhibitor) that reduced ethylene production and prolonged lifespan. Structural equation modeling showed that leaf lifespan had a negative effect on plant productivity, both directly and indirectly via its negative effect on net photosynthesis, across all 3years. Our results demonstrate the divergent responses of leaf lifespan and, in turn, plant productivity to warming under inter-annual and intra-annual precipitation variation, thus linking plant hormone production, functional traits and ecosystem functioning in the face of global environmental change.

Interannual oxygen isotope variability in Indian summer monsoon precipitation reflects changes in moisture sources

The primary influences on the spatio-temporal variability of oxygen isotope compositions in precipitation over the Indian summer monsoon domain are inadequately constrained by the limited observational record. Consequently, the climatic significance of isotopic signatures of precipitation preserved in proxy archives from the region remains unclear. Here we present simulations with an isotope-enabled climate model (IsoGSM2) with the moisture-tagging capability to investigate the role of relative contributions of moisture from oceanic and terrestrial sources to the interannual variability in oxygen isotope composition in summer monsoon rainfall. During weak monsoon years, the moisture contribution from the Arabian Sea dominates precipitation over the Indian subcontinent while the remote oceanic and terrestrial sources have a greater influence during strong monsoon years. We suggest that changes in monsoon circulation, moisture source, and precipitation intensity are interrelated and that speleothem oxygen isotope records from the region can potentially help reconstruct interannual to decadal monsoon rainfall variability.

Roles of water vapor sources and transport in the intraseasonal and interannual variation in the peak monsoon rainfall over East China

ERA-Interim reanalysis data from 1979 to 2017 are utilized to analyze the intraseasonal and interannual variabilities in the moisture transport associated with the summer rainfall over East China. Three key issues of moisture sources for East China summer precipitation are discussed in this study: the identification of the primary moisture sources of summer precipitation, determination of their individual contributions to the intraseasonal variation in summer precipitation, and determination of the extent to which each source affects the interannual variation in precipitation during the peak monsoon rainfall period (PMRP). Through the Lagrangian method, the water vapor is divided into six sources, namely, the land area source, East China source (EC source, except for the target region), Indian Ocean source (IO source), Pacific Ocean source, South China Sea source, and regional evapotranspiration sources. This study proposes that the rainfall over South China during the PMRP is mainly influenced by the IO source water vapor transport (52.4%). For the middle and lower Yangtze River valley, the rainfall contribution from southwesterly moisture transport accounts for approximately 50% of the total rainfall during the PMRP and determines the intraseasonal and interannual variation in the summer rainfall. The water vapor from terrestrial evaporation, which includes EC source water vapor (38.9%) and North China (NC) source water vapor (21.8%), is the most important moisture source for rainfall over NC during the PMRP.

Beyond the mean: long-term variabilities in precipitation and temperature on the Qinghai-Tibetan Plateau

AbstractLong-term variabilities in daily precipitation and temperature are critical for assessing the impacts of climate change on ecosystems. We characterized intra- and interannual variabilities in daily precipitation and temperature obtained from 1960 to 2015 at 78 meteorological stations on the Qinghai-Tibetan Plateau. The results show that 1) The intra-annual variability of daily precipitation increases for 55 meteorological stations with a rate of 0.08 mm per decade. In contrast, the intra-annual variability markedly decreases for daily mean, daytime mean, and nighttime mean temperatures with a rate of 0.09, 0.07, and 0.12 °C per decade, respectively at 90% or more of stations. 2) Variabilities of daily precipitation and temperatures are quite sensitive to high altitudes (> 3500 m). The intra- and interannual variabilities of daily precipitation significantly decrease at 1.0 and 0.07 mm per 1000 m, respectively. However, variations of high altitudes increase the intra- and interannual variabilities of daily mean temperature at 1.0 °C and 0.2 °C per 1000 m. Moreover, the interannual variability of nighttime mean temperature varies at 0.3 °C per 1000 m, the fastest rate among three temperature indices. 3) A larger mean annual precipitation is accompanied by a higher intra- and interannual variability of daily precipitation on the Qinghai-Tibetan Plateau; however, a higher mean annual temperature leads to lower variabilities of daily temperatures. This study illustrates that long-term climatic variability is understudied in alpine ecosystems characterized by high climatic sensitivity. Precipitation and temperature variabilities should be characterized to improve predictions of vulnerable ecosystems responding to climate change.

Outcomes of facilitative plant interactions in shrublands of NW Patagonia, Argentina

AbstractAimsThis study examined the plant–plant interaction networks and analyzed to what extent different nurse species groups with different traits (evergreen and deciduous) mediate the outcomes of the facilitated species composition.LocationFour shrublands located in Nahuel Huapi National Park, in Northern Patagonia, Argentina (41°11'55.34" S, 71°19'43.07" W).MethodsWe selected 10 woody species as nurse species: five evergreens and five deciduous species. We recorded species composition and total cover below nurse species and in open spaces during two consecutive years, with different interannual precipitation variability. We determined the facilitated species with the relative interaction intensity in plants (RII) index, constructed facilitation networks, and analyzed the species composition below nurses and in open spaces.ResultsIn our networks, nurse and facilitated species are generalist species. The species composition below the nurse canopies and open areas varied between years. The structure and parameters of networks built on two consecutive years were similar. However, we found changes in plant species interactions between the studied years. The species composition of the facilitated species growing below the deciduous and evergreen nurse species groups was similar.ConclusionsOur findings provide insights into knowledge of the facilitation networks in Patagonian shrublands. We found that networks were not nested and had many generalist species (nurses and facilitated). This implies that the disappearance of any nurse species would not change the community maintenance.

Impacts of land use conversion on the response of soil respiration to precipitation in drylands: A case study with four-yearlong observations

Soil respiration (Rs) in drylands is strongly influenced by precipitation. However, there is a lack of long-term studies on how land-use conversion impact the Rs's responds to precipitation variations. In situ Rs, soil moisture and soil temperature were monitored in cropland, and cropland converted jujube orchard, grassland and shrubland in the semiarid Loess Plateau, China for four years with significant interannual precipitation variation. Q10-soil moisture relationships were quantified by selecting observations within limited range of soil moisture. As soil moisture increased, Rs was found to be markedly suppressed in cropland and jujube orchard with great disturbance, with volumetric water content exceeding 0.15 and 0.16, respectively, but increased in grassland and shrubland with few disturbances. Q10 became saturated as soil moisture increased in cropland, and was linearly correlated with soil moisture in jujube orchard, grassland and shrubland. Q10 was least sensitive to soil moisture variation in shrubland, which was characterized by a nitrogen-fixing shrub. The interannual variation in mean growing season Rs (MGR) was positively correlated with mean soil moisture. The difference in MGR between land-use types was significant except during the extreme drought year: converting cropland to jujube orchard saw a reduction in MGR by 5–18%, while converting cropland to grassland and shrubland saw an increase in MGR by 16–53% and 67–126%, respectively. This corresponded with a greater sensitivity of MGR to soil moisture in grassland and shrubland. These results suggest a greater response of soil carbon emission in the land-use applied with afforestation or restoration to the enhanced soil moisture as precipitation intensify, compared to agricultural land-use.

Climate change impacts on precipitation and temperature in Prince Edward Island, Canada

AbstractTo understand climate change impacts on Prince Edward Island (PEI), Canada, historical daily precipitation and temperature of the island was investigated between the periods: 1931–60 (1940s), 1961–90 (1970s), and 1991–2020 (2000s) in its eastern, central, and western parts. Observed climatic data were utilized, augmented by some validated modeled data of Pacific Climate Impact Consortium (PCIC) for missing years. Statistically significant warming of the island was found ranging from 1.14°C in the east to 0.75°C in the west from the 1970s to 2000s. The warming trend during the period was distributed throughout the year including winters. In the east, mean monthly temperature significantly increased in all the months except for January, March, and June. Significant increase in temperature was found solely during August (+0.80°C) in central, and for August (+0.64°C), September (+0.99°C), and October (+0.73°C) in western parts. Proportionate increase in annual minimum temperature was greater than the maximum, particularly in eastern (+1.57°C) and central (+0.75°C) parts and thus indicated moderated cold there. Over the same 30‐year period, annual precipitation increased 6 percent in the east but decreased 5 and 8 percent in the central and the western PEI, respectively. The changes in precipitation were not statistically significant, except snowfall reduction (−20%) in the west, which was a statistically significant change. Interannual precipitation variations during wet and dry years having 20 and 80 percent probabilities of exceedance, respectively, ranged 350–470 mm/year during 1991–2020. Rainfall intensities, measured by hourly data, increased from 1.15 to 2.24 mm/hr, on average in central and western parts, respectively, in 2004–17 compared to 1970s. Impacts of the rising temperatures, decreasing precipitation, and uneven and intense rainfalls patterns on water resources and rainfed agriculture need further investigations. Climate change adaptations be included in existing water policies to mitigate the impacts.

Antarctic Atmospheric River Climatology and Precipitation Impacts

AbstractThe Antarctic ice sheet (AIS) is sensitive to short‐term extreme meteorological events that can leave long‐term impacts on the continent's surface mass balance (SMB). We investigate the impacts of atmospheric rivers (ARs) on the AIS precipitation budget using an AR detection algorithm and a regional climate model (Modèle Atmosphérique Régional) from 1980 to 2018. While ARs and their associated extreme vapor transport are relatively rare events over Antarctic coastal regions (∼3 days per year), they have a significant impact on the precipitation climatology. ARs are responsible for at least 10% of total accumulated snowfall across East Antarctica (localized areas reaching 20%) and a majority of extreme precipitation events. Trends in AR annual frequency since 1980 are observed across parts of AIS, most notably an increasing trend in Dronning Maud Land; however, interannual variability in AR frequency is much larger. This AR behavior appears to drive a significant portion of annual snowfall trends across East Antarctica, while controlling the interannual variability of precipitation across most of the AIS. AR landfalls are most likely when the circumpolar jet is highly amplified during blocking conditions in the Southern Ocean. There is a fingerprint of the Southern Annular Mode (SAM) on AR variability in West Antarctica with SAM+ (SAM−) favoring increased AR frequency in the Antarctic Peninsula (Amundsen‐Ross Sea coastline). Given the relatively large influence ARs have on precipitation across the continent, it is advantageous for future studies of moisture transport to Antarctica to consider an AR framework especially when considering future SMB changes.

Projection of the Precipitation Extremes in Thailand Under Climate Change Scenario RCP8.5

This study explores the predicted extreme precipitation during 2020–2029 in Thailand, using the output of the nested regional climate model (NRCM) with the Representative Concentration Pathway (RCP) 8.5 emission scenario. The research used five different extreme precipitation indices, i.e., annual precipitation total (PRCPTOT), the annual number of rainy days (RD), simple daily intensity index (SDII), consecutive dry days (CDDs), and consecutive wet days (CWD). The PRCTOT was generally located in eastern Thailand, with significant declining trends, while the increasing trend was found in northern Thailand. The quantity of the PRCPTOT varies marginally from 100 to 200 mm per decade. The annual RD was influenced mostly by the negative trends in Thailand. A remarkable trend is a rising of annual SDII, with major statistical increases ranging from 5 to 20%. A widespread decline in CWD was found in most regions. The statistically significant pattern of CWD has been geographically concentrated in the northern, southern, and eastern regions of Thailand. Southern Thailand continues to decline by −10 to −30%. A drastic decline has been observed in the south of Thailand. Projected interannual precipitation variability shows that December–January–February (DJF) variability will be greater than either annual or June–July–August (JJA) variability in most years, with the exception of 2022, 2025, and 2026, in which the JJA variability will be greater than both the annual variability and the DJF variability.

Predicting the Interannual Variability of California's Total Annual Precipitation

AbstractUnderstanding and predicting precipitation characteristics on seasonal and longer timescales can help California prepare for long‐term droughts and precipitation extremes. We find that interannual variations in total precipitation across California are primarily determined by precipitation frequency. As was shown previously for total precipitation, the precipitation frequency is linked to the North Pacific jet stream location. This indicates that California precipitation frequency is primarily controlled by where the jet guides precipitate weather systems rather than how moist or energetic the systems are. The jet's position, in turn, depends on the states of the El Niño‐Southern Oscillation (ENSO) and of the Pacific Decadal Oscillation (PDO). We use this to construct a regression model that predicts variations in California's annual total precipitation and precipitation frequency. Up to 20% of the wintertime precipitation variance in Southern California is predictable using decorrelated ENSO and PDO indices in the previous summer.

Interdecadal Changes in the Impact of the Philippine Sea Anticyclone on Boreal Winter Precipitation in Southwestern China

AbstractIn the last two decades, southwestern China (SWC) has experienced severe droughts, which are always accompanied by severe deficiencies in precipitation. In this study, we found that the interannual variability in boreal winter precipitation in SWC is modulated by the Philippine Sea anomalous anticyclone (PSAC). The interannual relationship between the PSAC and SWC precipitation experienced an interdecadal change around the early 1980s. The correlation between them was enhanced in the period from 1981 to 2001 (P2) compared to the period from 1961 to 1980 (P1). In P1, the moisture transported by the PSAC mainly affected eastern China, as the PSAC was located over the northern Philippine Sea, and the moisture budget of SWC was dominated by moisture transport at the western boundary. The PSAC, however, strengthened and shifted southwestward in P2, accompanied by a deepened India-Burma trough. As such, the PSAC transported moist air from the western North Pacific and the Indian Ocean into SWC through its southern boundary. Meanwhile, the stronger PSAC in P2 was accompanied by an upper-level convergence from the western North Pacific to the Bay of Bengal, which induced an upper-level divergence and ascending motion over SWC. Thus, the PSAC caused a significant increase in precipitation in P2. Stronger air-sea interactions in the western North Pacific induced by the El Niño–Southern Oscillation may be responsible for the enhancement and southwestward shift of the PSAC in P2 compared to that in P1.

CMIP6 Evaluation and Projection of Temperature and Precipitation over China

This article evaluates the performance of 20 Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating temperature and precipitation over China through comparisons with gridded observation data for the period of 1995–2014, with a focus on spatial patterns and interannual variability. The evaluations show that the CMIP6 models perform well in reproducing the climatological spatial distribution of temperature and precipitation, with better performance for temperature than for precipitation. Their interannual variability can also be reasonably captured by most models, however, poor performance is noted regarding the interannual variability of winter precipitation. Based on the comprehensive performance for the above two factors, the “highest-ranked” models are selected as an ensemble (BMME). The BMME outperforms the ensemble of all models (AMME) in simulating annual and winter temperature and precipitation, particularly for those subregions with complex terrain but it shows little improvement for summer temperature and precipitation. The AMME and BMME projections indicate annual increases for both temperature and precipitation across China by the end of the 21st century, with larger increases under the scenario of the Shared Socioeconomic Pathway 5/Representative Concentration Pathway 8.5 (SSP585) than under scenario of the Shared Socioeconomic Pathway 2/Representative Concentration Pathway 4.5 (SSP245). The greatest increases of annual temperature are projected for higher latitudes and higher elevations and the largest percentage-based increases in annual precipitation are projected to occur in northern and western China, especially under SSP585. However, the BMME, which generally performs better in these regions, projects lower changes in annual temperature and larger variations in annual precipitation when compared to the AMME projections.

Five Decades of Observed Daily Precipitation Reveal Longer and More Variable Drought Events Across Much of the Western United States

AbstractMultiple lines of evidence suggest climate change will result in increased precipitation variability and consequently more frequent extreme events. These hydroclimatic changes will likely have significant socioecological impacts, especially across water‐limited regions. Here we present an analysis of daily meteorological observations from 1976 to 2019 at 337 long‐term weather stations distributed across the western United States (US). In addition to widespread warming (0.2 °C ± 0.01°C/decade, daily maximum temperature), we observed trends of reduced annual precipitation (−2.3 ± 1.5 mm/decade) across most of the region, with increasing interannual variability of precipitation. Critically, daily observations showed that extreme‐duration drought became more common, with increases in both the mean and longest dry interval between precipitation events (0.6 ± 0.2, 2.4 ± 0.3 days/decade) and greater interannual variability in these dry intervals. These findings indicate that, against a backdrop of warming and drying, large regions of the western US are experiencing intensification of precipitation variability, with likely detrimental consequences for essential ecosystem services.

High-resolution dynamical downscaling of ERA-Interim temperature and precipitation using WRF model for Greece

This study presents the results of high-resolution dynamical downscaling of 5 km on maximum (TX) and minimum (TN) air temperature and precipitation, for Greece, with the Weather Research and Forecasting (WRF) model. The ERA-Interim (ERA-I) reanalysis dataset is used for initial and boundary conditions. The model results (WRF_5) are evaluated against available ground observations for the period 1980–2004 through the calculation of mean climatology, statistical metrics, and distributions of extreme events on daily, monthly and seasonal scales. WRF_5 model captures very well the geographical distribution of TX and TN of the study area, and illustrates finely the seasonal differences. Statistical results for TX (TN) indicate a cold (warm) bias of − 0.6 °C (1 °C) regarding WRF_5 and − 3 °C (0.5 °C) for ERA-I. The efficiency metrics for temperatures showed a highly improved performance of the model compared to reanalysis for all temporal scales investigated. The observed mean annual cycle and inter-annual variability of precipitation are also well represented by model simulation. Although WRF_5 overestimates rainfall during most of the year, the seasonal pattern of WRF_5 presented similar correlation coefficients for all stations with a range of 0.6–0.85, showing a good model ability to simulate the precipitation in Greece. The results reveal the capability of the configured WRF high resolution model to reproduce the main climatological variables of the study area, outperforming the coarse resolution ERA-Interim in a region that is dominated by highly variable topographic characteristics. This is deemed necessary for undertaking any further studies concerning future climate change impacts in various sectors.

Reconstructing Extreme Precipitation in the Sacramento River Watershed Using Tree‐Ring Based Proxies of Cold‐Season Precipitation

AbstractExtreme precipitation and consequent floods are some of California's most damaging natural disasters, but they are also critical to the state's water supply. This motivates the need to better understand the long‐term variability of these events across the region. This study examines the possibility of reconstructing extreme precipitation occurrences in the Sacramento River Watershed (SRW) of Northern California using a network of tree‐ring based moisture proxies across the Western US. We first develop a gridded reconstruction of the cold‐season standardized precipitation index (SPI) west of 100°W. We then develop an annual index of regional extreme precipitation occurrences in the SRW and use elastic net regression to relate that index to the gridded, tree‐ring based SPI. These regressions, built using SPI data across the SRW only and again across a broader region of the Western US, are used to develop reconstructions of interannual variability in extreme precipitation frequency back to 1400 CE. The SPI reconstruction is skillful across much of the West, including the Sacramento Valley and Central Oregon. The reconstructed SPI also captures historical interannual variations in extreme SRW precipitation, although individual events may be under‐ or over‐estimated. The reconstructions show more SRW extremes from 1580 to 1700 and 1850 to 1915, a dearth of extremes prior to 1550, and a 2–8 year oscillation after 1550. Using tree‐ring proxies beyond the SRW often dampens the reconstructed extremes, but these data occasionally help to identify known extreme events. Overall, reconstructions of SRW extreme precipitation can help to understand better the historic variability of these events.

남한지역에서의 관측 지중온도의 기후학적 특성 및 변동경향

Soil temperature (SoT) is one of the important climate elements for the land-atmosphere interactions. In this study, the climatic characteristics and trends of SoT were analyzed at nine locations for the period of 1966 to 2020. In addition, effect of precipitation on the interannual variations of SoT was also addressed. The monthly average of the SoT shows seasonal and interannual variations regardless of location. While there are some differences depending on the location and depth, the interannual variations of SoT occur more strongly at the shallow layer during summer comparatively other seasons. The strong negative correlation between SoT and precipitation of summer shows that the large interannual variations of SoT in summer is closely related to the strong interannual variations of precipitation of same season. According to the depth the range of SoT is larger in winter and summer and smaller in spring and autumn. Generally, air temperature and SoTs are increasing due to global warming. However, the increasing trend varies and depends on the location and depth of the study area. Most of investigation stations are revealed a strong increasing trend, particularly, at the shallow layer during summer season.

Interannual variation in summer extreme precipitation over Southwestern China and the possible associated mechanisms

AbstractThis study explores the spatial–temporal variations in summer extreme precipitation over Southwestern China (SWC). The frequency of summer extreme precipitation (FEP) has exhibited strong interannual variation with slightly strengthened intensity in recent decades. The associated anomalous water vapour transport mainly originates from northern China, the Indian Ocean, the South China Sea and the Northwest Pacific. The high FEP over SWC is generally associated with the strong Eurasian (EU) pattern and the pattern that is similar to Pacific‐Japan (PJ) teleconnection. The results further indicate that the anomalous May Arctic sea ice concentration and the sea surface temperature anomaly over the Northwest Pacific play an important role in the variation of FEP over SWC. On the one hand, the reduction in Arctic sea ice concentration intensifies Rossby wave propagation and then stimulates the formation of EU teleconnection pattern. The associated anomalous northeasterly integrated water vapour transport and high‐level westerly anomalies can result in strong interannual changes in FEP over SWC. On the other hand, the sea surface temperature anomaly over the Northwest Pacific can induce an anomalous PJ‐like pattern, and the associated anomalous southwesterly water vapour transport also exerts an impact on the change in FEP over SWC.

Interannual ice mass variations over the Antarctic ice sheet from 2003 to 2017 were linked to El Niño-Southern Oscillation

Interannual variability in the ice mass balance over the Antarctic Ice Sheet (AIS) is closely related to atmospheric circulation and has large impact on estimating the secular trends of mass change. However, the spatiotemporal patterns of the interannual mass balance over the AIS have not been well characterized and their connection with atmospheric circulation remains unclear. To address this limitation, we applied a statistical method to three sets of mass balance data and extracted the interannual mass change signals over the Antarctic Peninsula (AP), the West Antarctic Ice Sheet (WAIS), the East Antarctic Ice Sheet (EAIS), and the whole AIS from 2003 to 2017. Our results reveal that the interannual mass variations over the AP and the WAIS displayed similar temporal patterns, characterized by an increase in 2003-2008, a decrease in 2009-2013, and an increase again in 2014-2016 (relative to the mean of the interannual mass variations in 2003-2017). The interannual mass variations over the EAIS showed opposite patterns, characterized by a decrease in 2003-2008, an increase in 2009-2013, and a decrease again in 2014-2016. These temporal patterns generated a maximum value and a minimum value; the peak-to-valley mass change was −14 Gt for the AP and −129 Gt for the WAIS while the valley-to-peak mass change was 149 Gt for the EAIS. The entire AIS did not exhibit similar patterns to the WAIS or the EAIS but demonstrated oscillations of about three years. We find that the interannual variation in precipitation is the reason for the interannual variation of the mass balance over the AIS and was highly correlated with El Niño-Southern Oscillation (ENSO) in 2003-2017. The interannual precipitation was positively correlated with ENSO in the AP (correlation=0.8) and the WAIS (correlation=0.9) but negatively correlated in the EAIS (correlation=-0.8). We also uncover that ENSO largely modulated the atmospheric circulation over the AIS and its surrounding regions. In 2009-2013 when ENSO was in strong negative phase, precipitation decreased in the AP and the WAIS but increased in the EAIS, conversely, in 2014-2016 when ENSO was in strong positive phase, precipitation increased in the AP and the WAIS but decreased in the EAIS. Overall, the opposite behaviors of precipitation in the WAIS and the EAIS under strong ENSO conditions explained the spatiotemporal patterns of interannual ice mass variations over the AIS in 2003-2017. The findings of the anti-correlation between the ENSO and the precipitation in the EAIS and the opposite temporal patterns between the WAIS and the EAIS are particularly novel and adds new insights to cryosphere studies.

Historical and future climates over the upper and middle reaches of the Yellow River Basin simulated by a regional climate model in CORDEX

Despite the importance of the Yellow River to China, climate change for the middle reaches of the Yellow River Basin (YRB) has been investigated far less than for other regions. This work focuses on future changes in mean and extreme climate of the YRB for the near-term (2021–2040), mid-term (2041–2060), and far-term (2081–2100) future, and assesses these with respect to the reference period (1986–2005) using the latest REgional MOdel (REMO) simulations, driven by three global climate models (GCMs) and assuming historical and future [Representative Concentration Pathway (RCP) 2.6 and 8.5] forcing scenarios, over the CORDEX East Asia domain at 0.22° horizontal resolution. The results show that REMO reproduces the historical mean climate state and selected extreme climate indices reasonably well, although some cold and wet biases exist. Increases in mean temperature are strongest for the far-term in winter, with an average increase of 5.6 °C under RCP 8.5. As expected, the future temperatures of the warmest day (TXx) and coldest night (TNn) increase and the number of frost days (FD) declines considerably. Changes to mean temperature and FD depend on elevation, which could be explained by the snow-albedo feedback. A substantial increase in precipitation (34%) occurs in winter under RCP 8.5 for the far-term. Interannual variability in precipitation is projected to increase, indicating a future climate with more extreme events compared to that of today. Future daily precipitation intensity and maximum 5-day precipitation would increase and the number of consecutive dry days would decline under RCP 8.5. The results highlight that pronounced warming at high altitudes and more intense rainfall could cause increased future flood risk in the YRB, if a high GHG emission pathway is realized.