Interannual Variability Of Precipitation Research Articles

Coupled Model Intercomparison Project phase 5 and 6 representation of peak and end of rainy season over Upper Blue Nile basin

AbstractThe Upper Blue Nile river basin (uBN) is vital to three countries' water, food, and energy security (Ethiopia, Sudan, and Egypt). It is also a region with substantial interannual precipitation variability and the potential for significant climate change in coming decades. The El Niño–Southern Oscillation (ENSO) affects both variability and trends in uBN precipitation, with El Niño episodes historically connected with below‐average rainfall. In this context, this study seeks to: (a) examine the representation of ENSO–uBN rainfall teleconnections in simulations from the sixth Coupled Model Intercomparison Project (CMIP6), as compared to the previous generation of models (CMIP5); (b) distinguish between teleconnections during the peak of the rainy season (July–August [JA]) and the agriculturally critical end‐of‐season rains (September–October [SO]); (c) investigate evidence for Tropical Easterly Jet (TEJ) mediation of these teleconnections in CMIP6 versus CMIP5 and for both peak rains and end of the rainy season. Using a subset of high performing models, we find that CMIP6 simulations of uBN precipitation show somewhat less bias than CMIP5 for JA total rainfall, and that correlations with ENSO have become more consistent across models, but that differences between CMIP5 and CMIP6 are modest. CMIP6 simulations, like CMIP5, overestimate SO rainfall and suggest a stronger ENSO association in SO than is indicated by observations. Model representation of the TEJ and its association with both ENSO and uBN precipitation show no systematic change between CMIP5 and CMIP6. The mediating influence of the TEJ appears to be more important in JA than SO.

Nitrate losses across 29 Iowa watersheds: Measuring long-term trends in the context of interannual variability.

In the U.S. Corn Belt, annual croplands are the primary source of nitrate loading to waterways. Long periods of fallow cause most nitrate loss, but there is extreme interannual variability in the magnitude of nitrate loss due to weather. Using mean annual (2001-2018) flow-weighted nitrate-N concentration (FWNC; mg NO3 - -N L-1 ), load (kg NO3 - -N), and yield (kg NO3 - -N ha-1 cropland) for 29 watersheds, our objectives were (a) to quantify the magnitude and interannual variability of 5-yr moving average FWNC, load, and yield; (2) to estimate the probability of measuring 41% reductions in nitrate loss after isolating the effect of weather on nitrate loss by quantifying the interannual variability of nitrate loss in watersheds where there was no trend in 5-yr moving average nitrate loss (Iowa targets a 41% nitrate loss reduction from croplands); and (c) to identify factors that, in the absence of long-term trends in nitrate loss, best explain the interannual variability in nitrate loss. Averaged across all watersheds, the mean probability of measuring a statistically significant 41% reduction in FWNC across 15 yr, should it occur, was 96%. However, the probabilities of measuring 41% reductions in nitrate load and yield were only 44 and 32%. Across watersheds, soil organic matter, tile drainage, interannual variability of precipitation, and watershed area accounted for interannual variability in these nitrate loss indices. Our results have important implications for setting realistic timelines to measure nitrate loss reductions against the background of interannual weather variation and can help to target monitoring intensity across diverse watersheds.

Climate predictors and climate change projections for avian haemosporidian prevalence in Mexico.

Long-term, inter-annual and seasonal variation in temperature and precipitation influence the distribution and prevalence of intraerythrocytic haemosporidian parasites. We characterized the climatic niche behind the prevalence of the three main haemosporidian genera (Haemoproteus, Plasmodium and Leucocytozoon) in central-eastern Mexico, to understand their main climate drivers. Then, we projected the influence of climate change over prevalence distribution in the region. Using the MaxEnt modelling algorithm, we assessed the relative contribution of bioclimatic predictor variables to identify those most influential to haemosporidian prevalence in different avian communities within the region. Two contrasting climate change scenarios for 2070 were used to create distribution models to explain spatial turnover in prevalence caused by climate change. We assigned our study sites into polygonal operational climatic units (OCUs) and used the general haemosporidian prevalence for each OCU to indirectly measure environmental suitability for these parasites. A high statistical association between global prevalence and the bioclimatic variables ‘mean diurnal temperature range’ and ‘annual temperature range’ was found. Climate change projections for 2070 showed a significant modification of the current distribution of suitable climate areas for haemosporidians in the study region.

Atmospheric River activities and their effects on precipitation over South Korea

Atmospheric rivers (ARs) have been recognized as the main mechanism of water supply to many coastal regions across the globe, and large fractions of extreme precipitation events have been attributed to them in coastal landforms. Though more than 70% boundary of South Korea is coastal, the research literature on ARs and their impacts on precipitation is scarce, if not absent. In this study, we aim to explore the AR activity over South Korea and estimate their seasonal and spatial impact on the precipitation and its extremes over the region. To this end, we use gridded reanalysis data for identifying ARs and a recently developed high-resolution precipitation dataset for South Korea. As results, we find that ARs are an important source of precipitation over South Korea by occurring in all seasons, though their frequency varies significantly across the seasons. Further, we conclude that more than half of precipitation extremes may be attributed to ARs, and most of the top-ten extreme precipitation events witnessed by South Korea happen concurrently with ARs, especially in winter and spring seasons. Lastly, our analysis indicates that recent the changes in inter-annual variations of winter precipitation may be attributed to the strengthening of AR contributions, implying that more research on ARs and their impacts in a warmer world is critical for the region. Overall, our findings demonstrate that ARs are one of the main mechanisms of oceanic moisture inflow into South Korea, which will likely have important implications to water management in the country, through targeted forecasting of ARs and by utilizing the information in climate mechanism-based water planning and management.

Community leaf dry matter content predicts plant production in simple and diverse grassland

AbstractPlant growth correlates with values of collinear (covarying) traits from the leaf economics spectrum. Environmental variation and differences in community composition may alter contributions of these traits to plant production and thereby limit the consistency of trait‐based growth predictions among years and plant communities. We tested effects of interannual variation in precipitation and differences in grassland community composition (planted monoculture of switchgrass, Panicum virgatum, and mixture of perennial herbaceous species) on the utility of two traits from the leaf economics spectrum (leaf dry matter content [LDMC] and plant [N]) to predict aboveground net primary production (ANP) during spring of 6 years. Spatial and temporal variation in spring production correlated with community‐scale (species abundance‐weighted) values of both traits, but community LDMC explained 66% of the variance in production and accounted for ≥89% of the variance explained by the two traits combined. The ANP response to trait variation and the variance in ANP explained by trait values differed with precipitation and between communities. Greater precipitation increased the production response to trait variation by increasing slopes of ANP–trait regression relationships and increased the variance in ANP explained by trait values. Communities differed in response to precipitation variation and in the role of annual variation in the [N]–LDMC relationship in explaining variance in ANP. Results indicate that mean trends in grassland production can be predicted using community‐scale values of LDMC. Trait‐based predictions of grassland production could be improved, however, by accommodating precipitation and community effects on production–trait relationships.

Coupling reconstruction of atmospheric hydrological profile and dry-up risk prediction in a typical lake basin in arid area of China

Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation.

Future changes in precipitation over the upper Yangtze River basin based on bias correction spatial downscaling of models from CMIP6

Global climate change will change the temporal and spatial distribution of precipitation, as well as the intensity and frequency of extreme precipitation. The Yangtze River basin is one of the world’s largest basins, and understanding the future precipitation changes should be vital to flood control, water resources supply, and hydropower electricity generation in this basin. In this study, projected future characteristics of precipitation are analyzed in the upper Yangtze river basin (UYRB). To this end, based on the observed data from national meteorological stations, the bias correction spatial downscaling (BCSD) of five models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) is carried out. Then, based on the results of multi model ensemble (MME), we find that, relative to the historical period (1988–2014), the mean annual precipitation in the whole UYRB during 2015–2064 increases by 4.23%, 1.11%, 1.24% under SSP1-2.6, SSP2-4.5, SSP5-8.5, respectively, and it increases more in the long term (2040-2064) than that in the near term (2015–2039). Under SSP1–2.6, the precipitation will increase more significantly, which means lower emission of aerosols and greenhouse gases may increase the risk of flood disaster in the future over the UYRB. Interdecadal precipitation variability is more intense than interannual precipitation variability. Future precipitation changes in four seasons are spatially heterogeneous under three scenarios. Three extreme precipitation indices, including R95p, Rx1day and R10 mm, generally increase in the UYRB. R95p and Rx1day increase more in the WR and YBYCR basins with relatively high mean annual precipitation than that in other three sub-basins. R10 mm changes slightly in all sub-basins. The results reveal that the lower region of the UYRB may face greater risk of extreme precipitation. This study provides a timely updated finding about future changes in precipitation in the UYRB based on more accurate climate projections and ground-based observation.

Spring Extreme Precipitation Days in North China and Their Reliance on Atmospheric Circulation Patterns during 1979–2019

Abstract The interannual variation of springtime extreme precipitation (SEP) days in North China (NC) and their reliance on atmospheric circulation patterns are studied by using the continuous daily record of 396 rain gauges and the fifth generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis during 1979–2019. The SEP days are defined as the days when at least 10% of rain gauges in NC record daily precipitation no less than 10.5 mm. Results show that the number of SEP days shows large interannual variability but no significant trend in the study period. Using the objective classification method of the obliquely rotated principal analysis in T-mode, we classify the atmospheric circulation into five different patterns based on the geopotential height at 700 hPa. Three circulation patterns all have fronts and are associated with strong southerly wind, leading to 88% of SEP days in NC. The strong southerly wind may provide moisture and dynamic forcing for the frontal precipitation. The interannual variation of SEP days is related with the number of the three above-mentioned dominant circulation patterns. Further analysis shows that the West Pacific pattern could be one of the possible climate variability modes related to SEP days. This study reveals that the daily circulation pattern may be the linkage between SEP days and climate variability modes in NC. Significance Statement Springtime extreme precipitation (SEP) has important social and economic impacts on North China (NC), but few studies have examined the variation of SEP in NC. We find that the number of SEP days has no significant trend but shows large interannual variability during 1979–2019. The interannual variation of SEP days is mainly determined by the total days of three frontal circulation patterns associated with strong southerly wind. Based on the daily circulation pattern, the West Pacific pattern is found to be one of the possible climate variability modes related to SEP days. These findings may shed light on the understanding of SEP in midlatitudes around the world.

Inter-Annual Variations of Precipitation Modulate the Dry Spell Length.

Dry spell length (DSL), consecutive non‐rainy days between two precipitation events, play an important role in regulating soil moisture dynamics, terrestrial energy exchange as well as vegetation growth. According to the Clausius‐Clapeyron (C‐C) relationship, global warming can result in prolonged DSL. However, usually the amount of precipitation and its characteristics coincidentally varied with the changes of DSL under global warming, it remains unclear how the inter‐annual variation of precipitation interacts with the evolution of dry spells. In this study, the global long‐term in‐situ observation data set of daily precipitation during 1976–2019 was used to examine the spatiotemporal trends of growing season DSL and precipitation. Our results showed that the global mean growing season DSL significantly increased by 0.3 days decade−1 during 1976–1998 while no significant trend of that was observed during 1999–2019. In contrast, the growing season precipitation (Prec_GS) showed no significant trend in 1976–1998 whereas significant increase trend of that was observed in 1999–2019. To explore the impacts of precipitation on the evolution of dry spells, we examined the relationship between the growing season DSL and Prec_GS. We found that prevalent negative relationship was observed between growing season DSL and Prec_GS in 88% and 86% stations during the period of 1976–1998 and 1999–2019, respectively. Spatially, the mean annual Prec_GS and DSL showed significantly negative relationship, that is, the stations with more precipitation showed shorter DSL in growing season, and vice versa. The changes of mean annual Prec_GS explained 81% spatial variation of growing season DSL. Moreover, during the period of 1999–2019 significant increase of precipitation frequency and decrease of dry day frequency were also observed in addition to the increase of Prec_GS in this period. The decreased dry day frequency further resulted in the decrease of growing season DSL. By excluded the impacts of precipitation, the DSL/Prec_GS ratio showed significant decreasing trend during 1999–2019. Our study suggested that the spatiotemporal variations of DSL were modulated by the variation of precipitation. The impacts of precipitation changes on ecosystem by altering the dry spell evolution should be considered in modeling the terrestrial carbon and hydrological cycling in response to climate changes.

Compound Effects of Climate Change on Future Transboundary Water Issues in the Middle East

AbstractThe Middle East is one of the world's most vulnerable areas to climate change, which has exacerbated environmental, agricultural, water conflict, and public health issues in the region. Here we analyze the latest climate model projections of precipitation and temperature for the very high emissions scenario, SSP5‐8.5, to detect potential future changes in this region. A baseline period (1981–2010) is compared with the middle (2040–2069) and end (2070–2099) of the 21st century. The results, representing the worst‐case scenario, identify the Tigris‐Euphrates headwaters as the hotspot of future compounding effects of climate change in the Middle East. Those effects result from the coincidence of elevated temperature, reduced precipitation, and enhanced interannual variability of precipitation. The hotspot overlays the location of the Southeastern Anatolia Project (in Turkish, Güneydoğu Anadolu Projesi [GAP]) irrigation initiative. In this climate context, risks to GAP viability and downstream water security, and associated potential for water‐related conflicts and migration are considerable and demand a reconsideration of the risk‐benefit assessment of GAP. This need has become more urgent after the recent widespread and deadly climate‐related conflicts and wildfires in summer 2021 across the Middle East that further underlined vulnerability of the region to climate extremes.

Climatic Change Characteristics towards the “Warming–Wetting” Trend in the Pan-Central-Asia Arid Region

In recent years, the warming–wetting trend in the arid region of Northwest China has attracted widespread attention. To reveal whether this phenomenon exists in the whole Pan-Central-Asia arid region, this paper adopts the latest monthly gridded dataset of the Climate Research Unit Time Series version 4.05 (CRU TS v4.05) and the multi-model ensemble data of the Coupled Model Intercomparison Project Phase 6 (CIMP6) for discussion from multiple perspectives. The results show that the Pan-Central-Asia arid region has been getting warmer and wetter in the last 80 years. Since the turn of the 21st century, there has been an apparent slowdown in the regional wetting trend despite the acceleration of precipitation increase, mainly caused by the growth in evapotranspiration potential. The interannual scale dominates the precipitation change, including significant quasi-three-year and quasi-six-year cycles. The interannual variability in precipitation is mainly affected by the change in the phases of Pacific decadal oscillation (PDO), while long-term variation dominates the temperature change, which is significantly related to the variations in the Arctic oscillation (AO). Thus, future research and predictions of regional precipitation should focus on the PDO variations, followed by the Southern Oscillation Index (SOI), whereas for research on, and predictions of, temperature, the effect of AO variations should be emphasized. Except for a few regions in Central-Eastern Mongolia and Central Kazakhstan, precipitation levels in most parts of the Pan-Central-Asia region have been increasing. The regional temperature exhibits a distribution pattern which decreases from northwest to southeast. The increase in precipitation in the Pan-Central-Asia arid region alleviates the drought in most regions, including most of Northwest China. However, the arid and semi-arid climate patterns in this region have not changed. The warming–wetting trend will significantly accelerate in medium-emissions scenarios in the next 80 years. Although the increase in precipitation may be a positive aspect of this trend, the rise in potential evapotranspiration caused by sharp warming may cause greater challenges to the regional climate and ecological environment.

A novel Budyko-based approach to quantify post-forest-fire streamflow response and recovery timescales

Recent increases in the incidences of wildfires have necessitated the development of methodologies to quantify the effect of these fires on streamflows. Climate variability has been cited as a major challenge in revealing the true contribution of disturbance to streamflow changes. To address this, we developed an annual Budyko “decomposition” method for (1) statistical change detection of hydrologic signatures post-fire, (2) separating climate-driven and fire-driven changes in streamflow, and (3) estimating hydrologic recovery timescales after fire. We demonstrate the use of this methodology for 17 watersheds in Southern California with high interannual variability in precipitation. We show that while traditional metrics like changes in flow or runoff ratio might not detect a disturbance effect due to confounding climate signals, the Budyko framework can be used successfully for statistical change detection. The Budyko approach was also found to be robust in detecting changes in 5 highly burned catchments (>40% burned area ratio), while changes in less burned (2) and unburned catchments (10) were insignificant. We further used the Budyko approach to quantify the contribution of fire-driven versus climate driven changes in streamflow and found that fire contributed to an average increase in streamflow on the order of 80 mm yr−1, though the effect varied greatly between years. Finally, we estimated hydrologic recovery timescales that varied between 5 and 45 years for four burned catchments. We found a significant linear relationship between recovery time and burned area at medium and high severity for our study catchments, with about 4 years of recovery time per 10% of the watershed burned.

Mechanisms Controlling Carbon Sinks in Semi‐Arid Mountain Ecosystems

AbstractFeedbacks between the intertwined water and carbon cycles in semi‐arid mountain ecosystems can introduce large uncertainties into projections of carbon storage. In this study, we sought to understand the influence of key mechanisms on carbon balances, focusing on an ecosystem whose complex terrain and large interannual variability in precipitation adds to its vulnerability to warming. We applied a dynamic vegetation‐ecosystem model (Lund‐Potsdam‐Jena General Ecosystem Simulator) to simulate water‐carbon interactions in the 104,512 km2 Mediterranean‐climate ecosystems of California's Sierra Nevada for 1950–2099. Our 48 scenarios include a combination of carbon dioxide (CO2) increase, air temperature change, and varying plant rooting depths. We found that with warming (+2 and +5°C), water limitations on growth and enhanced soil respiration reduce carbon storage; however, CO2 fertilization and associated enhanced water‐use efficiency offset this loss. Using the 4 km model resolution to capture steep mountain precipitation gradients, plus accounting for the several meters of actual root‐accessible water storage in the region, were also important. With warming accompanied by CO2 fertilization our projections show that the Sierra Nevada sequestering at least 200 Tg (2 kg m−2) carbon, versus carbon loss with warming alone. The increase reflects coniferous forests growing at high elevations, and some increase in broadleaved forests at low‐to‐intermediate elevations. Importantly, uncertainty in fire disturbance could shift our finding from carbon sink to source. The improved mechanistic understanding of these feedbacks can advance modeling of carbon‐water interactions in mountain‐ecosystem under a warmer and potentially drier climate.

A Weak Precipitation Sensitivity of Glacier Runoff

AbstractA clear understanding of the influence of glaciers on the climate sensitivity of catchment runoff is critical to unravel the ongoing and future changes in runoff regimes of glacierized catchments in a warming climate. We demonstrate that irrespective of the climate setting, annual glacier runoff is relatively insensitive to the precipitation variability. A temperature‐dependent runoff from the glaciers and a precipitation‐dependent runoff from the non‐glacierized parts determine the climate response of the runoff of glacierized catchments at different time scales. The buffering effect of glaciers against extreme droughts and the multidecadal runoff peak in catchments with shrinking glaciers, both follow from the above properties of glacier runoff. The empirically observed “glacier‐compensation effect” is caused by an inhibited (amplified) response of the catchment runoff to the interannual precipitation (temperature) variability due to the glaciers present in the catchment.

Long-term regional changes in inter-annual precipitation variability in the Campania Region, Southern Italy

Precipitation variability in space and time has been a focus of research over the past decades. The largest body of literature was essentially focused on long-term changes in average climates and in climate extremes. Analyses of the changes in the inter-annual climate variability (the year-to-year variability), which represent an index of climatic risk, received instead very less attention, but it represents an important issue in order to quantitatively measure the socioeconomic impact of climate change impact over water resources. In order to depict a general characterization of the long-term climate variability for the Campania region, located in Southern Italy within the Mediterranean basin, an analysis of the precipitation coefficient of variation, assumed as an index of inter-annual climate variability, was performed over the period 1918–2015 and compared with the annual precipitation regime and the intra-annual precipitation variability of the same region. The Mann–Kendall and the modified Mann–Kendall tests were applied to detect the sign and significance of the temporal changes and Sen’s test was applied to quantify the temporal changes in inter-annual variability. The results illustrated a generalized condition (73% of total stations) of statistically significant increase of inter-annual variability distributed almost over the whole analyzed area, even though the detected change appeared rather moderate in magnitude. The relationship between annual precipitation, intra-annual precipitation variability, and inter-annual precipitation variability was not clearly identified for the studied region, likely because of the characteristics of climatic homogeneity for the area under investigation. However, the comparative analyzes clearly showed how, if the variations in the annual precipitation regime and in the intra-annual precipitation variability are poorly significant (respectively for 9% and 11% of total station), changes in inter-annual precipitation variability are strongly marked over the studied region.

Evaluating soil erosion by introducing crop residue cover and anthropogenic disturbance intensity into cropland C-factor calculation: Novel estimations from a cropland-dominant region of Northeast China

The black-land in Northeast China is one of three black-lands in the world and has become the largest grain producing area and commercial grain base of China. Therefore, black-land soil erosion caused by natural factors and human activities has attracted much attention. The Revised Universal Soil Loss Equation (RUSLE) developed by the Agriculture Research Service of the United States Department of Agriculture provides a comprehensive framework for assessing soil erosion and has been widely applied all over the world. Compared with factors such as rainfall erosivity, soil erodibility, topography, and conservation practice, the vegetation coverage and management factor (C-factor in RUSLE) of cropland encompasses the most easily optimized measures. However, in some studies, the quantification of C-factor only considers vegetation cover and ignores other farmland management measures due to the limitation of field management information at regional scale, which implies a huge room for improvement in quantification of C-factor. In this study, the quantification of C-factor considered not only vegetation cover but also crop residue cover, agricultural machinery total power, and fertilizer application rate. Among them, the former is related to weakening soil erosivity, and the latter two are related to enhancing soil erosivity. Monitored sediment transport modulus (STM) at the sub-watershed scale was used to compare changes in the estimation accuracy of the soil erosion modulus (SEM) before and after improving the C-factor. The results showed that the improved cropland C-factor in RUSLE produced a better linear fit accuracy between SEM and STM, with an average increase of 0.115 for R2. Moreover, the order of SEM from high to low in different years was: 12.01 t·ha−1·y−1 (2019), 11.43 t·ha−1·yr−1 (2005), 11.17 t·ha−1·yr−1 (2010), 11.01 t·ha−1·yr−1 (2015), and 10.30 t·ha−1·yr−1 (2000), which was positively correlated with interannual variation of precipitation in Northeast China. Spatially, the order of multi-year average SEM in agricultural zones from high to low was as follows: 22.53 t·ha−1·yr−1 (Liaoning Plain and Hilly Zone; LPH), 20.44 t·ha−1·yr−1 (Baekdu Mountain Zone; BM), 15.11 t·ha−1·yr−1 (Western Liao River Zone; WLR), 11.36 t·ha−1·yr−1 (Lesser Khingan Mountain Zone; LKM), 7.56 t·ha−1·yr−1 (Greater Khingan Mountain Zone; GKM), 3.41 t·ha−1·yr−1 (Sanjiang Plain Zone; SJP), 3.14 t·ha−1·yr−1 (Songnen Plain Zone; SNP), and 2.06 t·ha−1·yr−1 (Hulunbuir Grassland Zone; HG), whereas the soil loss amount from high to low in various agricultural zones was in the order of BM > LPH > WLR > GKM > LKM > SNP > SJP > HG. Our study verified the feasibility of improving the C-factor of croplands in areas where cropland is the dominant land-use type. Moreover, our method will contribute to the use of RUSLE with higher precision in other regional-scale soil erosion assessments worldwide.

Increased interannual precipitation variability enhances the carbon sink in a semi‐arid grassland

Abstract The amplifying interannual precipitation variability has been observed globally and is projected to intensify under climate change scenarios. However, its impacts on terrestrial vegetation and carbon (C) sink have not been well investigated. As part of a field manipulative experiment with three precipitation variabilities (20%, 40% and 60%) in a semi‐arid grassland, this study was conducted to examine the responses of ecosystem C cycling to increased precipitation variability. Across the 3 experimental years from 2010 to 2012, amplified precipitation variability enhances gross primary productivity (GPP) and ecosystem respiration (ER), as both GPP and ER were more sensitive to above‐ than below‐average precipitation. In addition, the larger responses of GPP than ER to precipitation variability resulted in an enhancement of net ecosystem productivity (NEP), such that NEP increased with the increasing precipitation variability. More species with higher sensitivity to increased precipitation under wet conditions and the insensitivity of root growth to decreased precipitation could largely be responsible for the above observations, which suggest that the semi‐arid grassland was more sensitive to wet treatment yet strongly resistant to drought. Our results provide empirical evidence that intensified precipitation variability could stimulate grassland C sink. The findings revealed in this study could facilitate the mechanistic understanding and imply the potential positive feedback of climate variability‐terrestrial C sink. Read the free Plain Language Summary for this article on the Journal blog.

Physical processes of summer extreme rainfall interannual variability in Eastern China—part II: evaluation of CMIP6 models

Eastern China is regularly exposed to extreme precipitation with significant socio-economical consequences. Following an observational analysis in a first part of this study, here the ability of the Coupled Model Intercomparison Project Phase 6 models to reproduce the main modes of interannual variability of 5-day summer extreme precipitation over eastern China is evaluated, using an empirical orthogonal teleconnection (EOT) method. These models capture the main patterns and magnitudes of the different EOT patterns, although the North China mode is less well represented. Models also reproduce the dynamical features associated with each mode. There is no systematic improvement in the ability of models to simulate either the pattern or the 5-day intensity when using higher resolution models compared to coarser resolution ones. Instead, multi-member or multi-model ensembles lead to results closer to observations. Using a low mitigation projection pathway (SSP-370), it is shown that the risk of the most extreme 5-day precipitation events by about 40%, 80% and more than 150% for global-mean warming levels, relative to 1850–1900, of + 1.5, + 2 and + 3 ^{circ }C respectively. This increase is found to be more significant for 5-days events than for seasonal scale precipitation, consistent with previous studies.

Aquifer recharge in the Piedmont Alpine zone: historical trends and future scenarios

Abstract. The spatial and temporal variability of air temperature, precipitation, actual evapotranspiration (AET) and their related water balance components, as well as their responses to anthropogenic climate change, provide fundamental information for an effective management of water resources and for a proactive involvement of users and stakeholders, in order to develop and apply adaptation and mitigation strategies at the local level. In this study, using an interdisciplinary research approach tailored to water management needs, we evaluate the past, present and future quantity of water potentially available for drinking supply in the water catchments feeding the about 2.3 million inhabitants of the Turin metropolitan area (the former Province of Turin, north-western Italy), considering climatologies at the quarterly and yearly timescales. Observed daily maximum surface air temperature and precipitation data from 1959 to 2017 were analysed to assess historical trends, their significance and the possible cross-correlations between the water balance components. Regional climate model (RCM) simulations from a small ensemble were analysed to provide mid-century projections of the difference between precipitation and AET for the area of interest in the future CMIP5 scenarios RCP4.5 (stabilization) and RCP8.5 (business as usual). Temporal and spatial variations in recharge were approximated with variations of drainage. The impact of irrigation, and of snowpack variability, on the latter was also assessed. The other terms of water balance were disregarded because they are affected by higher uncertainty. The analysis over the historical period indicated that the driest area of the study region displayed significant negative annual (and spring) trends of both precipitation and drainage. Results from field experiments were used to model irrigation, and we found that relatively wetter watersheds in the northern and in the southern parts behave differently, with a significant increase of AET due to irrigation. The analysis of future projections suggested almost stationary conditions for annual data. Regarding quarterly data, a slight decrease in summer drainage was found in three out of five models in both emission scenarios. The RCM ensemble exhibits a large spread in the representation of the future drainage trends. The large interannual variability of precipitation was also quantified and identified as a relevant risk factor for water management, expected to play a major role also in future decades.

Synergistic effect of El Ni\xf1o and the North Pacific Oscillation on wintertime precipitation over Southeastern China and the East China Sea Kuroshio area

Wintertime precipitation in China is most pronounced over the southeastern area, and the Kuroshio in the East China Sea anchors a prominent precipitation band over the warm side of the sea surface temperature front. Previous studies have suggested that many factors contribute to the interannual variation of the precipitation over southeastern China (SC), whereas less attention has been paid to precipitation variability over the East China Sea Kuroshio (ECSK) area. This study focuses on the interannual variation of wintertime precipitation over the SC and ECSK areas. Empirical orthogonal function analysis reveals a spatially uniform pattern from SC to the ECSK area. Composite analysis shows that an El Niño event intensifies wintertime precipitation over our target region, and this effect is tripled when an El Niño follows a positive North Pacific Oscillation (NPO) event in the previous winter. The positive NPO event in the previous winter intensifies the El Niño event via the Victoria mode ocean bridge and the subsequent Bjerknes feedback. In comparison with single-factor El Niño events, a much weaker Walker cell induced by the joint event induces a much weaker regional Hadley cell through anomalous descending motion over the western tropical Pacific. The weakened regional Hadley circulation over the western Pacific directly enhances the precipitation over the SC and ECSK area. In this study, the synergistic effect of an El Niño event and a positive NPO event indicates that the influence of the El Niño event can be amplified by the positive NPO event in the previous winter.