Changes In Mean Precipitation Research Articles

Sensitivity of the global hydrological cycle to the altitude of stratospheric sulphate aerosol layer

Abstract Stratospheric aerosol geoengineering (SAG) has been proposed as one of the potential options to offset the impacts of anthropogenically induced climate change. Previous modelling studies have shown that the efficacy of the cooling via SAG increases with altitude of the aerosol layer. It has been also shown that the stratospheric heating associated with SAG could stabilize the tropical atmosphere and weaken the tropical hydrological cycle. Using a global climate model, we perform a systematic study by prescribing volcanic sulphate aerosols at three different altitudes (22 km, 18 km and 16 km) and assess the sensitivity of the global and tropical mean precipitation to the altitude. We find that even though the efficacy of cooling increases with altitude of the aerosol layer, the global and tropical mean precipitation changes are less sensitive to the height of the aerosol layer. This is because the magnitude of both the global and tropical mean precipitation reduction increases with aerosol altitude in response to increasing efficacy of aerosols, but this sensitivity related to the slow response is nearly offset by the sensitivity of fast precipitation adjustments to aerosol altitude. A perspective and analysis based on atmospheric energy budget is presented to explain the lack of sensitivity of the hydrological cycle to the altitude of the stratospheric sulphate aerosol layer.

Projected regional changes in mean and extreme precipitation over Africa in CMIP6 models

Precipitation plays a crucial role in Africa’s agriculture, water resources, and economic stability, and assessing its potential changes under future warming is important. In this study, we demonstrate that the latest generation of coupled climate models (CMIP6) robustly project substantial wetting over western, central, and eastern Africa. In contrast, southern Africa and Madagascar tend toward future drying. Under shared socioeconomic pathways (defined by Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5), our results suggest that most parts of Africa, except for southern Africa and Madagascar, will experience very wet years five times more often in 2050–2100, according to the multi-model median. Conversely, southern Africa and Madagascar will experience very dry years twice as often by the end of the 21st century. Furthermore, we find that the increasing risk of extreme annual rainfall is accompanied by a shift toward days with heavier rainfall. Our findings provide important insights into inter-hemispheric changes in precipitation characteristics under future warming and underscore the need for serious mitigation and adaptation strategies.

Projected Changes in Mean and Extreme Precipitation over Northern Mexico

Abstract Northern Mexico is home to more than 32 million people and is of significant agricultural and economic importance for the country. The region includes three distinct hydroclimatic regions, all of which regularly experience severe dryness and flooding and are highly susceptible to future changes in precipitation. To date, little work has been done to characterize future trends in either mean or extreme precipitation over northern Mexico. To fill this gap, we investigate projected precipitation trends over the region in the NA-CORDEX ensemble of dynamically downscaled simulations. We first verify that these simulations accurately reproduce observed precipitation over northern Mexico, as derived from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, demonstrating that the NA-CORDEX ensemble is appropriate for studying precipitation trends over the region. By the end of the century, simulations forced with a high-emissions scenario project that both mean and extreme precipitation will decrease to the west and increase to the east of the Sierra Madre highlands, decreasing the zonal gradient in precipitation. We also find that the North American monsoon, which is responsible for a substantial fraction of the precipitation over the region, is likely to start later and last approximately three weeks longer. The frequency of extreme precipitation events is expected to double throughout the region, exacerbating the flood risk for vulnerable communities in northern Mexico. Collectively, these results suggest that the extreme precipitation-related dangers that the region faces, such as flooding, will increase significantly by the end of the century, with implications for the agricultural sector, economy, and infrastructure. Significance Statement Northern Mexico regularly experiences severe flooding and its important agricultural sector can be heavily impacted by variations in precipitation. Using high-resolution climate model simulations that have been tested against observations, we find that these hydroclimate extremes are likely to be exacerbated in a warming climate; the dry (wet) season is projected to receive significantly less (more) precipitation (approximately ±10% by the end of the century). Simulations suggest that some of the changes in precipitation over the region can be related to the North American monsoon, with the monsoon starting later in the year and lasting several weeks longer. Our results also suggest that the frequency of extreme precipitation will increase, although this increase is smaller than that projected for other regions, with the strongest storms becoming 20% more frequent per degree of warming. These results suggest that this region may experience significant changes to its hydroclimate through the end of the century that will require significant resilience planning.

Analysis of recent trends and spatiotemporal changes of droughts over Serbia using high-resolution gridded data

The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E-OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia.

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Constraints on regional projections of mean and extreme precipitation under warming

The projected changes in the hydrological cycle under global warming remain highly uncertain across current climate models. Here, we demonstrate that the observational past warming trend can be utilized to effectively co1nstrain future projections in mean and extreme precipitation on both global and regional scales. The physical basis for such constraints relies on the relatively constant climate sensitivity in individual models and the reasonable consistency of regional hydrological sensitivity among the models, which is dominated and regulated by the increases in atmospheric moisture. For the high-emission scenario, on the global average, the projected changes in mean precipitation are lowered from 6.9 to 5.2% and those in extreme precipitation from 24.5 to 18.1%, with the inter-model variances reduced by 31.0 and 22.7%, respectively. Moreover, the constraint can be applied to regions in middle-to-high latitudes, particularly over land. These constraints result in spatially resolved corrections that deviate substantially and inhomogeneously from the global mean corrections. This study provides regionally constrained hydrological responses over the globe, with direct implications for climate adaptation in specific areas.

Storylines for Future Projections of Precipitation Over New Zealand in CMIP6 Models

AbstractLarge uncertainty exists in the sign of long‐term changes in regional scale mean precipitation across the current generation of global climate models. To explore the physical drivers of this uncertainty for New Zealand, here we adopt a storyline approach applying cluster analysis to spatial patterns of future projected seasonal mean precipitation change across CMIP6 models (n = 43). For the winter precipitation change signal, the models split roughly into two main groups: both groups have a very robust wet signal across the west coast of the South Island but differ notably in terms of the sign of precipitation change across the north of the North Island. These far north winter precipitation differences appear related to how far the Hadley cell edge and regional eddy‐driven jet shift across the models relative to their historical positions. In contrast, for summer, most models have a markedly weaker and spatially non‐uniform response, where internal variability often plays a large role. However, a small group of models predict a robust wet signal across most of the country in summer. This “wet model” group is characterized by a regional La Niña‐like increase in high pressure shifted further to the south‐east of New Zealand, associated with more frequent north‐easterly flow over the country and accompanied by significant warming of local sea surface temperatures. This regional circulation response appears related to changes in stationary Rossby wave paths as opposed to changes in La Niña occurrence frequency itself.

Lacustrine rhythmites from the Mulhouse Basin (Upper Rhine Graben, France): a sedimentary record of increased seasonal climatic contrast and sensitivity of the climate to orbital variations through the Eocene-Oligocene Transition

The Eocene-Oligocene Transition (EOT) marks the passage from Eocene greenhouse to Oligocene icehouse conditions. It holds keys to our understanding of the behavior of climate systems under major pCO2 shifts. While the environmental impact of the EOT is rather homogenous in oceans, it is much more heterogeneous on continents. Although little to no changes are recorded in some regions, several EOT studies in western Eurasia suggest an increase in seasonal climatic contrast (e.g., higher amplitude of changes in mean temperature or precipitation), along with a higher sensitivity of the climate to orbital variations. However, these variations remain to be properly documented through changes in sedimentary facies and structures and forcing mechanisms. Here we investigate the depocenter of the Mulhouse Basin (Upper Rhine Graben; URG) revealing a prominent transition from massive mudstones to laminated sediments and varves, alongside the emergence of astronomically-forced mudstone-evaporite alternations. These changes are identified in the distal and proximal parts of the southern URG, where they consist of millimeter-thick mudstone-evaporite couplets and siliciclastic-carbonate couplets. The elemental composition and micro-facies analysis of the laminae show a recurrent depositional pattern consistent with a seasonal depositional process, which suggests that they are varves. We propose that the occurrence of varved sediments, together with the observed orbital cyclicity in the southern URG, reflects an increase in seasonal climatic contrast, and an increase in the sensitivity of climate to orbital variations across the EOT. We show that similar changes were noticed in the Rennes and Bourg-en-Bresse basins, and that of other western Eurasian records for similar climatic conditions. This work emphasizes the potential of high-resolution sedimentary structures to serve as markers of climate change across the EOT.

Unveiling climate change impacts on agricultural sustainability: insights from the united states

Climate change poses significant threats to agricultural systems, necessitating a comprehensive understanding of its impact for effective adaptation strategies. This study examines the influence of climate change on agriculture in the United States, primarily focusing on temperature shifts and precipitation variations. Utilizing historical data and climate projections, we analyse trends in mean temperature and precipitation patterns from 1950 to 2020. The results indicate a noteworthy increase in annual mean temperature over the years, attributed to climate change. This rise in temperature has multifaceted implications, including heat stress in crops and exacerbation of drought conditions. The study also explores the complex relationship between precipitation patterns and climate change, highlighting regional variations and potential shifts in future precipitation trends. By projecting data under SSP 1-1.9 emission scenario, we assess potential changes in mean temperatures, hot days, and precipitation for 2040-2059 periods. In conclusion, this study sheds light on the interplay between climate change and agricultural systems, emphasizing the need for adaptive strategies to secure food production and mitigate potential risks. The findings underscore the urgency of proactive measures to safeguard agricultural sustainability and resilience in the face of evolving climatic conditions.

Precipitation Projection in Cambodia Using Statistically Downscaled CMIP6 Models

The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation strategies. Hence, future climate information is essential for developing effective strategies. This study explored the applicability of a statistical downscaling method, Bias-Corrected Spatial Disaggregation (BCSD), in downscaling climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and then applied the downscaled data to project the future condition of precipitation pattern and extreme events in Cambodia. We calculated four climate change indicators, namely mean precipitation changes, consecutive dry days (CDD), consecutive wet days (CWD), and maximum one-day precipitation (rx1day) under two shared socioeconomic pathways (SSPs) scenarios, which are SSP245 and SSP585. The results indicated the satisfactory performance of the BCSD method in capturing the spatial feature of orographic precipitation in Cambodia. The analysis of downscaled CMIP6 models shows that the mean precipitation in Cambodia increases during the wet season and slightly decreases in the dry season, and thus, there is a slight increase in annual rainfall. The projection of extreme climate indices shows that the CDD would likely increase under both climate change scenarios, indicating the potential threat of dry spells or drought events in Cambodia. In addition, CWD would likely increase under the SSP245 scenario and strongly decrease in the eastern part of the country under the SSP585 scenario, which inferred that the wet spell would have happened under the moderate scenario of climate change, but it would be the opposite under the SSP585 scenario. Moreover, rx1day would likely increase over most parts of Cambodia, especially under the SSP585 scenario at the end of the century. This can be inferred as a potential threat to extreme rainfall triggering flood events in the country due to climate change.

Dynamic and Thermodynamic Contributions to Late 21st Century Projected Rainfall Change in the Congo Basin: Impact of a Regional Climate Model’s Formulation

Addressing the impacts of climate change requires, first of all, understanding the mechanisms driving changes, especially at the regional scale. In particular, policymakers and other stakeholders need physically robust climate change information to drive societal responses to a changing climate. This study analyses late 21st-century (2071–2100) precipitation projections for the Congo Basin under representative concentration pathway (RCP) 8.5, using the Rossby Centre Regional Climate Model (RCM) RCA4. Specifically, we examine the impact of the RCM formulation (reduction of turbulent mixing) on future change in seasonal mean precipitation by comparing the results of the modified model version (RCA4-v4) with those of the standard version (RCA4-v1) used in CORDEX (Coordinated Regional Climate Downscaling Experiment). The two RCM versions are driven by two global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5). The results show that seasonal precipitation is largely affected by modifications in the atmospheric column moisture convergence or divergence, and, in turn, associated with changes in the dynamic (ΔDY) and thermodynamic (ΔTH) components of the moisture-budget equation. Projected decreased precipitation in the dry seasons (December–January–February and June–July–August) is linked to increased moisture divergence driven by dynamic effects (changes in circulation), with most experiments showing ΔDY as the main contributor (>60%) to the total moisture budget. Overall, precipitation is projected to increase in the wet seasons (March–April–May and September–October–November), which can be attributed to both dynamic and thermodynamic effects, but with a larger thermodynamic contribution (changes in specific humidity, ΔTH > 45%), compared to the dynamic one (ΔDY > 40%). Through a comparison of the two model versions, we found that the formulation (reducing turbulent mixing) and boundary conditions (driving GCM) strongly influence precipitation projections. This result holds substantial value for ensuring the fitness of models for future projections intended for decision-makers.

MIROC6 Large Ensemble (MIROC6-LE): experimental design and initial analyses

Abstract. Single model initial-condition large ensembles (LEs) are a useful approach to understand the roles of forced responses and internal variability in historical and future climate change. Here, we produce one of the largest ensembles thus far using the MIROC6 coupled atmosphere–ocean global climate model (MIROC6-LE). The total experimental period of MIROC6-LE is longer than 76 000 years. MIROC6-LE consists of a long preindustrial control run, 50-member historical simulations, 8 single forcing historical experiments with 10 or 50 members, 5 future scenario experiments with 50 members and 3 single forcing future experiments with 50 members. Here, we describe the experimental design. The output data of most of the experiments are freely available to the public. This dataset would be useful to a wide range of research communities. We also demonstrate some examples of initial analyses. Specifically, we confirm that the linear additivity of the forcing-response relationship holds for the 1850–2020 trends of the annual mean values and extreme indices of surface air temperature and precipitation by analyzing historical fully forced runs and the sum of single forced historical runs. To isolate historical anthropogenic signals of annual mean and extreme temperature for 2000–2020 relative to 1850–1900, ensemble sizes of 4 and 15, respectively, are sufficient in most of the world. Historical anthropogenic signals of annual mean and extreme precipitation are significant with the 50-member ensembles in 76 % and 69 % of the world, respectively. Fourteen members are sufficient to examine differences in changes in annual mean values and extreme indices of temperature and precipitation between the shared socioeconomic pathways (ssp), ssp585 and ssp126, in most of the world. Ensembles larger than 50 members are desirable for investigations of differences in annual mean and extreme precipitation changes between ssp126 and ssp119. Historical and future changes in internal variability, represented by departures from the ensemble mean, are analyzed with a focus on the El Niño/Southern Oscillation (ENSO) and global annual mean temperature and precipitation. An ensemble size of 31 is large enough to detect ENSO intensification from preindustrial conditions to 1951–2000, from 1951–2000 to 2051–2100 in all future experiments, and from low- to high-emission future scenario experiments. The single forcing historical experiments with 27 members can isolate ENSO intensification due to anthropogenic greenhouse gas and aerosol forcings. Future changes in the global mean temperature variability are discernible with 23 members under all future experiments, while 50 members are not sufficient for detecting changes in the global mean precipitation variability in ssp119 and ssp126. We also confirm that these temperature and precipitation variabilities are not precisely analyzed when detrended anomalies from the long-term averages are used due to interannual climate responses to the historical natural forcing, which highlights the importance of large ensembles for assessing internal variability.

Little Change in Apparent Hydrological Sensitivity at Large CO2 Forcing

AbstractApparent hydrological sensitivity (ηa), the change in the global mean precipitation per degree K of global surface warming, is a key aspect of the climate system's response to increasing CO2 forcing. To determine whether ηa depends on the forcing amplitude we analyze idealized experiments over a broad range of abrupt CO2 forcing, from 2× to 8× preindustrial values, with two distinct climate models. We find little change in ηa between 2× and 4×CO2, and almost no change beyond 5×CO2. We validate this finding under transient CO2 forcing at 1%‐per‐year, up to 8×CO2. We further corroborate this result by analyzing the 1%‐per‐year output of more than 15 CMIP5/6 models. Lastly, we examine the 1,000‐year long LongrunMIP model output, and again find little change in ηa. This wealth of results demonstrates that ηa is a very weak function of CO2 forcing.

A clustering-based multi-model ensemble projection of near-term precipitation changes over East China and its uncertainty

An ensemble of 28 models from the 6th Coupled Model Intercomparison Project was used to project future changes in annual mean precipitation over East China during 2046–2065 relative to 1995–2014 under the SSP2-4.5 scenario. A precipitation increase of 0.16 mm d−1 is projected over North China by the multi-model ensemble (MME) mean. However, large model uncertainty exists over South China (SC), reducing the fidelity of the MME mean projection. Thus, a clustering-based MME probabilistic projection is presented that projects four possible SC precipitation changes in the future. Precipitation increases are projected in Cluster 1, Cluster 3 and Cluster 4 for 0.51 mm d−1, 0.2 mm d−1 and 0.23 mm d−1, respectively, with occurrence probabilities of 14.3%, 35.7% and 25%, respectively. Conversely, the projected Cluster 2 precipitation decrease is 0.01 mm d−1 with an occurrence probability of 25%. The differences in precipitation change are mainly contributed by dynamic effect due to different circulation changes across clusters. During extended summer, different circulation anomalies over western North Pacific (WNP) among clusters arise from the sea surface temperature anomaly (SSTA) warming patterns over the equatorial central-eastern Pacific, which explain the different precipitation increases over SC. During extended winter, a strong zonal SSTA gradient between the South China Sea and adjacent WNP is projected in Cluster 2, stimulating a zonally vertical cell with anomalous descent over SC and resulting in markedly decreased precipitation. A similar but much weaker zonal SSTA gradient and circulation anomaly are projected in Cluster 3. Distinct meridional SSTA gradients over the WNP are projected in the rest clusters, stimulating shifted descents with a weak effect on SC precipitation.

Uncovering the primary drivers of regional variability in the impact of climate change on wheat yields in China

Responses of wheat yield in different regions to separate and joint changes in mean temperature (Tmean), precipitation (Prec), and solar radiation (Rad) are the foundation for sustainable development under climate change; however, these remain uncertain. Here, we quantified the response of wheat yield variation to changes in Tmean, Prec, and Rad by building multiple regression models, de-trending analysis, and MK trend tests. Multi-site meteorological data was obtained from different wheat growing areas and corresponding wheat yield data from provinces. Our findings showed that the effects of different climatic elements on wheat yield are spatially heterogeneous by region, and the combined effects of climatic elements are higher than those of single elements. Climate change caused an increase of 1% and 4.52% in winter and winter-spring wheat areas, respectively, and a loss of 3.72% in spring wheat areas. In addition, the effect of single meteorological factors on wheat yield varied depending on their rate of change. Rad and Prec are the main drivers of wheat yield variability; in winter, spring and winter-spring wheat areas, Rad significantly impacted wheat yield by 0.89%, −1.18%, and 2.46%, respectively, and Prec caused changes of −0.18%, −1.54%, and 1.33%, respectively. Considering normal and extreme climate fluctuations, we found that the contribution of climate change to wheat yield changes in different wheat-growing regions reached 26.1%, 18.6%, and 16.7%, respectively. Our results indicate that the overall climatic conditions in the spring wheat region are moving in an unfavourable direction, while Prec variability has become the main limiting factor for wheat production in the current winter and winter-spring wheat regions. These comprehensive and detailed findings provide a reference for the development of more accurate adaptation strategies and management measures in different regions. Going forward, the results of this study can be better applied to the development of region-specific climate-smart agricultural practices and extended to other crops and regions to better understand the broader impacts of climate change on global food security.

The Choice of Baseline Period Influences the Assessments of the Outcomes of Stratospheric Aerosol Injection

AbstractThe specifics of the simulated injection choices in the case of stratospheric aerosol injections (SAI) are part of the crucial context necessary for meaningfully discussing the impacts that a deployment of SAI would have on the planet. One of the main choices is the desired amount of cooling that the injections are aiming to achieve. Previous SAI simulations have usually either simulated a fixed amount of injection, resulting in a fixed amount of warming being offset, or have specified one target temperature, so that the amount of cooling is only dependent on the underlying trajectory of greenhouse gases. Here, we use three sets of SAI simulations achieving different amounts of global mean surface cooling while following a middle‐of‐the‐road greenhouse gas emission trajectory: one SAI scenario maintains temperatures at 1.5°C above preindustrial levels (PI), and two other scenarios which achieve additional cooling to 1.0°C and 0.5°C above PI. We demonstrate that various surface impacts scale proportionally with respect to the amount of cooling, such as global mean precipitation changes, changes to the Atlantic Meridional Overturning Circulation and to the Walker Cell. We also highlight the importance of the choice of the baseline period when comparing the SAI responses to one another and to the greenhouse gas emission pathway. This analysis leads to policy‐relevant discussions around the concept of a reference period altogether, and to what constitutes a relevant, or significant, change produced by SAI.

Projections of mean and extreme precipitation over China and their resolution dependence in the HighResMIP experiments

Projected near-future changes in mean and extreme precipitation by the end of the mid-21st century over China are investigated using the latest CMIP6 HighResMIP simulations grouped by different categories of horizontal and vertical resolutions. Evaluation of the historical simulations demonstrates improvements in the realism of the simulated precipitation over the different sub-regions with increased model resolutions. More apparent improvements are displayed by models with increased vertical resolution than those with increased horizontal resolutions. The near-future scenario of SSP5–8.5 suggests general increases in mean and extreme precipitation across Northwest and East-Northeast China. Also, models with coarser horizontal resolutions project an intensified precipitation seasonality over China. Models at relatively high vertical resolutions project decreased precipitation and enhanced droughts over Southwest China, while these are less apparent in models with relatively coarse vertical resolutions. All the simulations project a northward shift of summer and winter monsoon flows in East Asia. Meanwhile, a weaker summer monsoon across the tropics with a weakening of the monsoon trough over the South China Sea are projected. This indicates a less favorable environment for precipitation across the southern sub-regions. The complicated responses of precipitation to these environmental mechanisms are partly linked to the presented resolution-dependent uncertainties. Such uncertainties should be recognized and treated with caution in understanding the near-future hydrological changes in China.

How Credibly Do CMIP6 Simulations Capture Historical Mean and Extreme Precipitation Changes?

AbstractFuture precipitation changes are typically estimated from climate model simulations, while the credibility of such projections needs to be assessed by their ability to capture observed precipitation changes. Here we evaluate how skillfully historical climate simulations contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6) capture observed changes in mean and extreme precipitation. We find that CMIP6 historical simulations skillfully represent observed precipitation changes over large parts of Europe, Asia, northeastern North America, parts of South America and western Australia, whereas a lack of skill is apparent in western North America and parts of Africa. In particular in regions with moderate skill the availability of very large ensembles can be beneficial to improve the simulation accuracy. CMIP6 simulations are regionally skillful where they capture observed (positive or negative) trends, whereas a lack of skill is found in regions characterized by negative observed precipitation trends where CMIP6 simulates increases.

Changes in mean and extreme homogeneous precipitation in China during 1960–2020

This study aims to explore the observed national and regional changes in the seasonal mean and extreme precipitation in mainland China between 1960 and 2020 using data from 678 stations. Tests of homogeneity (e.g. standard normal homogeneity test, Pettitt's test and Buishand range test) are applied to identify homogeneous stations for the trend analysis. The non-parametric Mann-Kendall test and a modified Theil-Sen slope estimator were then used to examine changes in the precipitation characteristics. Our results show that despite a decreasing trend in the frequency of wet days, the mean precipitation has actually increased. Extreme precipitation has also increased, and in many locations, at greater rates than those of the mean. This is principally due to a greater rate of increase per degree of warming, of 8% for extreme precipitation compared to 7% for the mean. However, considerably regional and seasonal variability has been seen in the trends. Mean and extreme precipitation trends are positive throughout in western China for all seasons, but they vary in eastern China. Mean precipitation increased slightly in the southeast but decreased in the northeast of the country. Extreme precipitation increased in both regions, but the increases were greater in the southeast. Trends, additionally, also differed within regions, especially over eastern China. In southeast China, precipitation increased in the east and decreased in the west. In northeast China, precipitation increased in the north and decreased in the south. Using a multiple regression model, we found that changes during summer precipitation clearly dominate the overall annual changes in most regions. Most long-term changes over eastern China appear to be linked to those of the East-Asian and South-Asian Summer Monsoons.

Changes of mean and extreme precipitation and their relationship in Northern Hemisphere land monsoon domain under global warming

AbstractReliable projections of monsoon mean and extreme precipitation are vital to water resource management, disaster mitigation as well as policy makings. Since the climate models have better capability in projecting mean precipitation, the relationship between mean and extreme precipitation is a crucial clue for reliable projections of extreme precipitation. However, selections of optimal models in reproducing historical mean/extreme precipitation and their relationship were rarely reported. Here, more credible projections of mean/extreme precipitation and their connections over Northern Hemisphere land monsoon domain (NHLMD) were explored after a systematical assessment of the models from Coupled Model Intercomparsion Project Phase 6 (CMIP6) and CMIP5. Results indicated that most models could well reproduce the climatology and the variation of mean precipitation over NHLMD, while large portions have underestimated the extreme precipitation threshold (EPTH) and overestimated the extreme precipitation days (EPDs). However, nearly all models captured the observed robust relationships between mean and extreme precipitation. The projected mean precipitation and EPDs exhibit coherent variations with increase trend over Asian‐North African monsoon, and decrease trend over North American monsoon. The significant positive correlations between mean precipitation and EPDs will continue during 21st century. Considering the relatively low skills and large uncertainty in the simulation and the projection of EPDs, the tight connection could be used to reliably project the future extreme precipitation over the NHLMD using the projection of monsoon mean precipitation via the selected models.