Precipitation In Most Regions Research Articles

Decadal to centennial extreme precipitation disaster gaps — Long-term variability and implications for extreme value modelling

A material consequence of climate change is the intensification of extreme precipitation in most regions across the globe. The respective trend signal is already detectable at global to regional scales, but long-term variability still dominates local observational records, which are the basis for extreme precipitation risk assessment. Whether the frequency of extreme events is purely random or subject to a low-frequency internal variability forcing is therefore highly relevant for modelling the expected number of extreme events in a typical observational record. Based on millennial climate simulations, we show that long-term variability is largely random, with no clear indication of low-frequency decadal to multidecadal variability. Nevertheless, extreme precipitation events occur highly irregularly, with potential clustering (11% probability of five or more 100-year events in 250 years) or long disaster gaps with no events (8% probability for no 100-year events in 250 years). Even for decadal precipitation records, a complete absence of any tail events is not unlikely, as, for example, in typical 70-year observational or reanalysis data, the probability is almost 50%. This generally causes return levels – a key metric for infrastructure codes or insurance pricing – to be underestimated. We also evaluate the potential of employing information across neighbouring locations, which substantially improves the estimation of return levels by increasing the robustness against potential adverse effects of long-term internal variability. The irregular occurrence of events makes it challenging to estimate return periods for planning and for extreme event attribution.

Analysis of the relationship between dust aerosol and precipitation in spring over East Asia using EOF and SVD methods

This study utilized the Empirical Orthogonal Function (EOF) and Singular Value Decomposition (SVD) methods to investigate the spatial and temporal patterns and trends of dust aerosol and precipitation, and to identify the coupled modes between them. The research employed MODIS and CALIPSO retrieved dust aerosol optical depth (DAOD) data to represent dust aerosol information and CMORPH data to provide precipitation information. The results indicated that specific dust source regions were associated with the primary modes of spring dust in East Asia, while atmospheric circulation and land-sea monsoon were closely related to the primary modes of spring precipitation. Additionally, the study revealed that the impact of dust aerosol on precipitation varied based on the source region within the coupled modes. The first coupled mode, with dust sources in the Mongolian Gobi and Taklamakan Desert, demonstrated a pattern of increased dust aerosol and reduced precipitation in most regions. The second coupled mode, with dust sources focused on the Mongolian Gobi, exhibited a consistent pattern of increased dust aerosol and a significant increase in precipitation in northern China. This study highlights the significance of considering dust source regions when examining the relationship between dust aerosol and precipitation, providing new insights into the potential impact of dust aerosol on precipitation in East Asia during the spring.

Evaluation and Correction of Climate Simulations for the Tibetan Plateau Using the CMIP6 Models

This study evaluates the abilities of fifteen High-resolution Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate temperature and precipitation over the Tibetan Plateau (TP) for the years 1980–2014. The impacts of terrain correction and Empirical Orthogonal Function (EOF) correction on simulations of temperature and precipitation are examined. The results show that equal-weighted ensemble averaging of the CMIP6 high-resolution model provides a good representation of the spatial distribution of temperature over the TP, although simulations underestimate observations by 1.87 °C. The simulated spatial range of temperature cooling significantly exceeds the observed range, particularly in the central and southwestern TP. The performances of the simulations for precipitation are far poorer than those for temperature, and although the CMIP6 model represents the distribution of annual mean precipitation, simulations of precipitation show significant deviations from observations. Furthermore, model simulations of precipitation are 1.57 mm lower than observed, and 30% lower than observed in the southeastern TP. However, the CMIP6 model overestimated the intensity of precipitation in most regions, especially in the southeastern part of the TP. Meanwhile, the EOF analysis indicates that the effects of the correction of temperature exceed that of precipitation. Therefore, a range of methods should be considered for correcting temperature and precipitation over a complex terrain.

Empirical estimate of forestation-induced precipitation changes in Europe

Land-cover changes can affect the climate by altering the water and energy balance of the land surface. Numerous modelling studies have indicated that alterations at the land surface can result in considerable changes in precipitation. Yet land-cover-induced precipitation changes remain largely unconstrained by observations. Here we use an observation-based continental-scale statistical model to show that forestation of rain-fed agricultural land in Europe triggers substantial changes in precipitation. Locally, we find an increase in precipitation following forestation, in particular in winter, which is supported by a paired rain-gauge analysis. In addition, forests are estimated to increase downwind precipitation in most regions during summer. By contrast, the downwind effect in winter is positive in coastal areas but near neutral and negative in Continental and Northern Europe, respectively. The combined local and non-local effects of a realistic reforestation scenario, constrained by sustainability safeguards, are estimated to increase summer precipitation by 7.6 ± 6.7% on average over Europe (0.13 ± 0.11 mm d–1), potentially offsetting a substantial part of the projected precipitation decrease from climate change. We therefore conclude that land-cover-induced alterations of precipitation should be considered when developing land-management strategies for climate change adaptation and mitigation. Forestation over Europe triggers substantial local and downwind precipitation changes, according to results from an observation-based continental-scale statistical model.

The impact of teleconnections on the temporal dynamics in aboveground net primary productivity of the Mongolian Plateau grasslands

AbstractTemporal dynamics in aboveground net primary productivity (ANPP) are significant for environmental protection and economic development in the Mongolian Plateau grasslands (MPGs). Climate control of ANPP's temporal variations has intensified in response to local meteorological conditions, while the contributions of large‐scale atmospheric circulations to ANPP variations are poorly understood in the MPGs. First, we explored the temporal dynamics in annual ANPP, and then, we analyzed correlations among annual ANPP, local meteorological variables, and three different teleconnections during 1982–2015 in this study. Our analytical results indicated that (a) ANPP exhibited an increasing trend during the entire study period. However, the increasing trend did not persist, and two reversals occurred in 1998 and 2007. (b) ANPP variations were primarily influenced by summer precipitation in most regions and by summer precipitation and temperature together in other regions of the MPGs. (c) The Atlantic Multidecadal Oscillation (AMO) in winter negatively dominated annual ANPP variations by influencing summer precipitation and summer temperature in central Mongolia. The North Atlantic Oscillation (NAO) in winter exerted strong positive impacts on ANPP variations by influencing summer precipitation in Inner Mongolia, China. The East Atlantic Western Russia (EAWR) in spring controlled annual ANPP variations by influencing summer precipitation in western and eastern Mongolia. (d) The winter AMO, winter NAO and spring EAWR significantly dominated the annual ANPP variations in 49.78% of the MPGs, with values of 18.90, 9.81 and 21.07%, respectively. (e) Reversals of the winter AMO, winter NAO and spring EAWR between negative and positive phases resulted in two reversals of ANPP trends. This study will improve our understanding of the role of large‐scale atmospheric circulations in regulating ANPP variations and will be valuable in guiding the development of grazing land management in Mongolia and Inner Mongolia, China.

Effects of precipitation and temperature on precipitation use efficiency of alpine grassland in Northern Tibet, China

Precipitation use efficiency (PUE) is crucial in understanding the coupling between ecosystem carbon and water cycling. In this study, we used a time series (2000–2013) dataset of net primary productivity (NPP) based on the Carnegie–Ames–Stanford Approach (CASA) model together with precipitation to reveal the spatial and temporal patterns of alpine grassland PUE in Northern Tibet. The mean annual PUE values of alpine meadow, alpine meadow steppe, alpine steppe, alpine desert steppe, and alpine desert were 0.48, 0.39, 0.36, 0.29 and 0.23 gc m−2 mm−1, respectively. The spatial patterns of PUE of alpine grassland demonstrated an initial increase in the arid region and a subsequent decrease in the humid region along the precipitation gradient and peaked at approximately 500 mm. To evaluate the temporal patterns, the sensitivity Slope and the Pearson correlation coefficient {R}_{xy} between the PUE and climatic factors were calculated. The inter-annual variability of PUE exhibited a significant negative correlation with annual precipitation (P < 0.05), which implies that NPP had a lower sensitivity to precipitation in most regions. The relationship between PUE and the mean annual temperature is different for different regions. Our findings have an important role in understanding the impacts of precipitation availability on climate change and in the scientific management of the alpine grassland ecosystems.

Evaluation of Daily Precipitation Product in China from the CMA Global Atmospheric Interim Reanalysis

The China Meteorological Administration (CMA) recently produced a CMA Global Atmospheric Interim Reanalysis (CRAI) dataset for the years 2007–2016. A comprehensive evaluation of the ability of CRAI to capture the spatiotemporal variability of observed precipitation, in terms of both mean states and extreme indicators over China, is performed. Comparisons are made with other current reanalysis datasets, namely, the ECMWF interim reanalysis (ERAI), Japanese 55-yr reanalysis (JRA55), NCEP Climate Forecast System Reanalysis (CFSR), and NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), as well as NCEP Climate Prediction Center (CPC) observations. The results show that, for daily variations of rainfall during warm seasons in eastern China, CRAI and CFSR overestimate the precipitation of the main rain belt, while the overestimation is confined to the area south of 25°N in JRA55 but north of 24°N in MERRA2; whereas ERAI tends to underestimate the precipitation in most regions of eastern China. Two extreme metrics, the total amount of precipitation on days where daily precipitation exceeds the 95th percentile (R95pTOT) and the number of consecutive dry days (CDDs) in one month, are examined to assess the performance of reanalysis datasets. In terms of extreme events, CRAI, ERAI, and JRA55 tend to underestimate the R95pTOT in most of eastern China, whereas more frequent extreme rainfall can be found in most regions of China in both CFSR and MERRA2; and all of the reanalyses underestimate the CDDs. Among the reanalysis products, CRAI and JRA55 show better agreement with the observed R95pTOT than the other datasets, with fewer biases, higher correlation coefficients, and much more similar linear trend patterns, while ERAI stands out in better capturing the amount and temporal variations of the observed CDDs.

Responses of soil moisture to regional climate change over the Three Rivers Source Region on the Tibetan Plateau

AbstractIn this study, soil moisture data from two reanalysis datasets (ERA‐Interim, ERA5), a satellite soil moisture product from the European Space Agency (ESA) and three assimilation datasets from the Global Land Data Assimilation System (GLDAS), that is, GLADS‐NOAH025, GLADS‐NOAH10, and GLDAS‐CLM were compared with the observed soil moisture data in Maqu and Maduo stations over the Three Rivers Source Region (TRSR) on the Tibetan Plateau in China. Comparative statistical parameters between the soil moisture observations and the products, including the root mean square error, correlation coefficient (R), and standard deviation ratio were calculated to evaluate the products in different seasons. It was found that most products overestimated the soil moisture values, among which GLADS‐NOAH025 had relatively good consistency with the observations in the surface soil layer (0–10 cm), whereas GLDAS‐CLM agreed well with the observations in the 10–40 cm layer. Both ERA5 and ERA‐interim soil moisture overestimated soil moisture at all levels. The responses of soil moisture to regional climate change over the TRSR were also investigated by using the GLDAS‐NOAH025 soil moisture product, the ESA soil moisture product, and the observations during the nonfreezing period. The results show that the trends of soil moisture are consistent with the precipitation changes in the main central part of the TRSR. A significant positive correlation was found between soil moisture and precipitation in most regions of the TRSR, which indicates that soil moisture increases with the increase of precipitation, except in the northwest TRSR, where the variation of soil moisture was possibly influenced by both the precipitation changes and the increase of evapotranspiration.

Intensification of precipitation extremes in the world’s humid and water-limited regions

Changes in precipitation totals and extremes are among the most relevant consequences of climate change, but in particular regional changes remain uncertain. While aggregating over larger regions reduces the noise in time series and typically shows increases in the intensity of precipitation extremes, it has been argued that this may not be the case in water-limited regions. Here we investigate long-term changes in annual precipitation totals and extremes aggregated over the world’s humid, transitional, and dry regions as defined by their climatological water availability. We use the globally most complete observational datasets suitable for the analysis of daily precipitation extremes, and data from global climate model simulations. We show that precipitation totals and extremes have increased in the humid regions since the mid-20th century. Conversely, despite showing tendencies to increase, no robust changes can be detected in the drier regions, in part due to the large variability of precipitation and sparse observational coverage particularly in the driest regions. Future climate simulations under increased radiative forcing indicate total precipitation increases in more humid regions but no clear changes in the more arid regions, while precipitation extremes are more likely to increase than to decrease on average over both the humid and arid regions of the world. These results highlight the increasing risk of heavy precipitation in most regions of the world, including water-limited regions, with implications for related impacts through flooding risk or soil erosion.

Inter-comparison of remotely sensed precipitation datasets over Kenya during 1998–2016

The paucity of reliable ground based datasets remains a major challenge over Kenya. In the advent of extreme wetness or drought events, reliable precipitation estimates for local characterization is a long overdue process. In the present study, four Satellite derived Precipitation Estimates (SPE): TMPA V7 3B42, PERSIANN-CDR, CHIRPS, and ARC2, are assessed over four homogeneous zones in Kenya with gauge based data during 1998–2016. Results show that variations of SPE products are based on complex geomorphology of different climatic zones. All SPE products depict bimodal annual precipitation pattern with west-east gradient representing heavier to lighter precipitation events. The Monthly analysis reveal good statistical agreement with reference datasets despite underestimation of precipitation in most regions. Seasonal precipitation events show that the PERSIANN-CDR perform better along low altitude humid climate and western zones around Lake Basin while ARC2 has uniform performance as gauge stations over highlands regions. Strong positive linear relationship on annual scale is evident in most SPE products with CHIRPS, ARC2, and TMPA exhibiting relatively high correlation (r) and minimum root mean square error (RMSE), except for PERSIANN-CDR. Overall, the findings of this study show the potentials of SPE products for applications over study domain. The TMPA V7 and PERSIANN-CDR could be useful in understanding individual floods events. Since the CHIRPS perform relatively well over ASAL regions, it could be utilized in monitoring droughts events.

Accuracy evaluation of two precipitation datasets over upper reach of Heihe River Basin, northwestern China

As an important forcing data for hydrologic models, precipitation has significant effects on model simulation. The China Meteorological Forcing Dataset (ITP) and Global Land Data Assimilation System (GLDAS) precipitation data are the two commonly used data sources in the Heihe River Basin (HRB). This paper focused on evaluating the accuracy of these two precipitation datasets. A set of metrics were developed to characterize the trend, magnitude, annual allocation, event matching, frequency, and spatial distribution of the two datasets. Meanwhile, such accuracy evaluation was performed at various scales, i.e., daily, monthly, and yearly. By comparing with observations, this study concluded that: first, both ITP and GLDAS precipitation data well represented the trends at corresponding sites, and GLDAS underestimated precipitation in most regions except the east tributary headwater region; second, unusual annual precipitation distribution was observed in both datasets with overestimation of precipitation in May through September and GLDAS appeared to be much severe; third, the ITP data seriously over-predicted the precipitation events; fourth, the ITP data have better spatial distribution than GLDAS in the upper reach area of HRB. Overall, we recommended ITP precipitation data for the land surface study in the upper reach of HRB.

Assessing the Robustness of Future Extreme Precipitation Intensification in the CMIP5 Ensemble

AbstractA warming climate is expected to intensify extreme precipitation, and climate models project a general intensification of annual extreme precipitation in most regions of the globe throughout the twenty-first century. We investigate the robustness of this future intensification over land across different models, regions, and seasons and evaluate the role of model interdependencies in the CMIP5 ensemble. Strong similarities in extreme precipitation changes are found between models that share atmospheric physics, turning an ensemble of 27 models into around 14 projections. We find that future annual extreme precipitation intensity increases in the majority of models and in the majority of land grid cells, from the driest to the wettest regions, as defined by each model’s precipitation climatology. The intermodel spread is generally larger over wet than over dry regions, smaller in the dry season compared to the wet season and at the annual scale, and largely reduced in extratropical compared to tropical regions and at the global scale. For each model, the future increase in annual and seasonal maximum daily precipitation amounts exceeds the range of simulated internal variability in the majority of land grid cells. At both annual and seasonal scales, however, there are a few regions where the change is still within the background climate noise, but their size and location differ between models. In extratropical regions, the signal-to-noise ratio of projected changes in extreme precipitation is particularly robust across models because of a similar change and background climate noise, whereas projected changes are less robust in the tropics.

Future shift of the relative roles of precipitation and temperature in controlling annual runoff in the conterminous United States

Abstract. This study examines the relative roles of climatic variables in altering annual runoff in the conterminous United States (CONUS) in the 21st century, using a monthly ecohydrological model (the Water Supply Stress Index model, WaSSI) driven with historical records and future scenarios constructed from 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. The results suggest that precipitation has been the primary control of runoff variation during the latest decades, but the role of temperature will outweigh that of precipitation in most regions if future climate change follows the projections of climate models instead of the historical tendencies. Besides these two key factors, increasing air humidity is projected to partially offset the additional evaporative demand caused by warming and consequently enhance runoff. Overall, the projections from 20 climate models suggest a high degree of consistency on the increasing trends in temperature, precipitation, and humidity, which will be the major climatic driving factors accounting for 43–50, 20–24, and 16–23 % of the runoff change, respectively. Spatially, while temperature rise is recognized as the largest contributor that suppresses runoff in most areas, precipitation is expected to be the dominant factor driving runoff to increase across the Pacific coast and the southwest. The combined effects of increasing humidity and precipitation may also surpass the detrimental effects of warming and result in a hydrologically wetter future in the east. However, severe runoff depletion is more likely to occur in the central CONUS as temperature effect prevails.

A new ensemble of GCM simulations to assess avoided impacts in a climate mitigation scenario

There is growing evidence that the role internal variability plays in our confidence in future climate projections has been under-appreciated in past assessments of model projections for the coming decades. In light of this, a 15 member ensemble has been produced to complement the existing 30 member “Large Ensemble” conducted with the Community Earth System Model (CESM). In contrast to the Large Ensemble, which explored the variability in RCP8.5, our new ensemble uses the moderate mitigation scenario represented by RCP4.5. By comparing outputs from these two ensembles, we assess at what point in the future the climates conditioned on the two scenarios will begin to significantly diverge. We find in general that while internal variability is a significant component of uncertainty for periods before 2050, there is evidence of a significantly increased risk of extreme warm events in some regions as early as 2030 in RCP8.5 relative to RCP4.5. Furthermore, the period 2061-2080 sees largely separate joint distributions of annual mean temperature and precipitation in most regions for the two ensembles. Hence, in the CESM’s representation of the Earth System for the latter portion of the 21st century, the range of climatic states which might be expected in the RCP8.5 scenario is significantly and detectably further removed from today’s climate state than the RCP4.5 scenario even in the presence of internal variability.

A comprehensive evaluation of precipitation simulations over China based on CMIP5 multimodel ensemble projections

AbstractPrecipitation variability has great economic, social, and environmental impacts across the globe, and in particular in China. This paper evaluates the historical precipitation variability based on 20 general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive over the 20th century relative to two observational data sets and quantifies CMIP5 improvements over CMIP3. Multimodel ensemble means and individual models are assessed. Three future emission scenarios are used (representative concentration pathways (RCP) 8.5, RCP 4.5, and RCP 2.6), and 21st century CMIP5 estimates are put into context based on the 20th century biases. We find that CMIP5 models can reproduce the spatial pattern of precipitation over China during the 20th century, which represents an improvement over CMIP3. However, the models overestimate the magnitude of seasonal and annual precipitation in most regions of China, especially along the eastern edge of the Tibetan Plateau, and underestimate summer precipitation over southeastern China. For China as a whole, CMIP5's overestimation of annual precipitation is greater than CMIP3, which can be traced back to a greater underestimation of summer precipitation in CMIP3. There is a large spread among individual models, with the greatest uncertainties in simulating summer precipitation. Trends and correlations also suggest a better agreement of CMIP5 with observations than CMIP3. Throughout the 20th century, both the observations and models show an increasing trend in precipitation over parts of northwestern China and a decreasing trend over the Tibetan Plateau. There is poor agreement in precipitation trends over the southeast and northeast regions. In general, multimodel means cannot capture the amplitude of observed multidecadal precipitation variability. In the 21st century, precipitation is generally projected to increase across all of China under all three scenarios. RCP 8.5 exhibits the largest significant trend at a rate of +1.5 mm/yr, corresponding to 16% precipitation increase by the end of the century. The RCP 2.6 scenario shows the smallest increases, at +0.5 mm/yr (6%) by 2100. The greatest increases are projected to occur over the Tibetan Plateau and eastern China in summer, suggesting an altered monsoonal circulation in the future. However, due to the uncertainties in CMIP5, future precipitation projections should be interpreted with caution.

中国南方冬季降水异常的时空分布特征分析

利用我国南方224个测站，近50a年平均地面降水资料，采用线性趋势分析、EOF、REOF、Mann-Kendall、合成分析等方法，分析了季风区冬季降水异常变化的规律。结果表明：1) 南方冬季降水自西向东递增，高值中心分别在湘东和江浙闽交界区，而在滇北川南有一干舌区，这个干舌区的存在可能是导致西南地区冬季易出现干旱的重要原因之一。近50a南方冬季降水以4.42 mm/10a的速率不显著增多，其中，1月以32.59 mm/10a的速率显著增多，12月和2月不显著。冬季降水经历了两个波动阶段：1960s~1970s中期偏多，1970s后期偏少；1980s~1990s后期以来偏多为主；冬季降水的稳定性，从南北向中部递增，在川东—黔北—湘中一带形成稳定中心。2) 大多数区域冬季降水变化有上升趋势，倾向率从西向东增大，在长江下游的有显著增多趋势，云贵高原有不显著减少趋势，其余地方降水变化趋势不显著增多。3) 冬季降水异常主要有3种分布模态：全区一致型、高原平原差异型和巫山型，这种分布与风场异常有关联。该区冬季降水异常主要分为华南区、长江中下游平原区、云贵高原区3个子区域。4) 各分区的异常干、湿冬年，华南和长江中下游大部分出现在1980年以后，但云贵高原比较分散；长江中下游在1988年有突变现象。各区降水的年际、年代变化差异较大，但进入本世纪都处于减少趋势。Using the mean surface precipitation data from 224 stations of southern China over the years of 1961-2010 and adopting the methods of linear regression analysis, multinomial fitting, EOF, REOF, Mann-Kendall and Glide T-examination etc., we analyzed the spatial anomaly features and time evolution rule of the winter precipitation in southern China. The results show that 1) China Southern winter precipitation increases from west to east; the high value centers are in eastern Hunan-border area of Jiangxi and Zhejiang and Fujian; while in northern Yunnan Southern Sichuan there has a dry tongue area, and the presence of this dry tongue area may lead to winter drought in south-west region. Southern winter precipitation increased slightly with a rate of 4.42 mm/10a in recent 50 years; it increased significantly in January with a rate of 32.59 mm/10a, but it was not significant in December and February. Winter precipitation fluctuations experienced two stages: above normal from 1960s to the mid-1970s, less than normal in the late 1970s; mainly above normal from 1980s to the late 1990s. Stability of winter precipitation increases from north and south to central areas. In eastern Sichuan-Guizhou-Hunan area, it forms a stable center. 2) As to the winter precipitation in most regions, there is an upward trend at a rate increasing from west to east. In the lower reaches of the Yangtze River, there has a significant increasing trend; there is no significant decreasing trend in Yunnan-Guizhou plateau. In the rest of places, precipi- tation trend was not significantly increased. 3) With the EOF method, the abnormity of southern winter precipitation can be divided into three kinds of distributed types, namely entire regional distribution type, plateau and plain opposite distribution type and Wushan type. This distribution may be related with wind anomaly. With the REOF method, the area can be subdivided into 3 sub-areas: the Southern China, the middle and low reach of Yangtze River and the Yunnan-Guizhou Plateau. 4) The dry and wet anomaly in winter, in Southern China and the middle and low reach of Yangtze River in each subarea occurred mostly after 1980, but scattered in Yunnan-Guizhou Plateau; There was a mutation phenomenon at the middle and low reach of Yangtze River in 1988. Inter-annual and decadal variations of the precipitation were greatly different in each subarea, but declined at the beginning of this century.

Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least.

Winter wheat yields in the UK: uncertainties in climate and management impacts

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 54:49-68 (2012) - DOI: https://doi.org/10.3354/cr01085 Winter wheat yields in the UK: uncertainties in climate and management impacts Kyungsuk Cho1,*, Pete Falloon2, Jemma Gornall2, Richard Betts2, Robin Clark2 1Korea Meteorological Administration, 61 Yeoeuidaebang-ro 16-gil, Dongjak-gu, Seoul 156-720, Korea 2Met Office Hadley Centre, Fitzroy Road, Exeter EX1 3PB, UK *Email: cks0716@korea.kr ABSTRACT: Winter wheat is an important UK cereal, suited to the current climate. However, recent climate projections show changes in temperature and precipitation are likely, potentially affecting UK crop yields. Assessments of future yields contain several sources of uncertainty including those associated with climate and potential adaptation. Here we address these uncertainties using the CERES-Wheat model fed with an ensemble of regional model projections and different sowing dates and fertiliser regimes. In all of the 13 administrative regions in the UK Climate Projections (UKCP09), increases in temperature accelerated the development rate of wheat, a result that was robust across the ensemble. This generally leads to positive impacts on yield and a northward shift in cultivation, with some decreases in the south. Uncertainties in yield became greater towards 2100, a result of corresponding increases in the uncertainty of climate changes. Sensitivity analysis suggests that CO2 fertilisation could compensate for yield losses due to changes in temperature and precipitation in most regions. Earlier sowings appear to be more beneficial in the future over the UK, whilst later sowings increase the risk of yield losses. In a warmer climate, increasing the amount of fertiliser did not improve yields and in fact increased the risk to productivity. Critically, adjustments to sowing date and fertiliser addition did not mitigate the loss of yield experienced in southern regions, suggesting limited adaptation potential in this case. We propose that regional yield changes may not be critical for wheat production in the UK as a whole, as losses in some regions are more than compensated for by gains in others. KEY WORDS: UKCP09 · SRES A1B · Uncertainty · CERES-Wheat · UK winter wheat · Yield Full text in pdf format PreviousNextCite this article as: Cho K, Falloon P, Gornall J, Betts R, Clark R (2012) Winter wheat yields in the UK: uncertainties in climate and management impacts. Clim Res 54:49-68. https://doi.org/10.3354/cr01085 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 54, No. 1. Online publication date: August 03, 2012 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2012 Inter-Research.

Elevation gradients of European climate change in the regional climate model COSMO-CLM

A transient climate scenario experiment of the regional climate model COSMO-CLM is analyzed to assess the elevation dependency of 21st century European climate change. A focus is put on near-surface conditions. Model evaluation reveals that COSMO-CLM is able to approximately reproduce the observed altitudinal variation of 2 m temperature and precipitation in most regions and most seasons. The analysis of climate change signals suggests that 21st century climate change might considerably depend on elevation. Over most parts of Europe and in most seasons, near-surface warming significantly increases with elevation. This is consistent with the simulated changes of the free-tropospheric air temperature, but can only be fully explained by taking into account regional-scale processes involving the land surface. In winter and spring, the anomalous high-elevation warming is typically connected to a decrease in the number of snow days and the snow-albedo feedback. Further factors are changes in cloud cover and soil moisture and the proximity of low-elevation regions to the sea. The amplified warming at high elevations becomes apparent during the first half of the 21st century and results in a general decrease of near-surface lapse rates. It does not imply an early detection potential of large-scale temperature changes. For precipitation, only few consistent signals arise. In many regions precipitation changes show a pronounced elevation dependency but the details strongly depend on the season and the region under consideration. There is a tendency towards a larger relative decrease of summer precipitation at low elevations, but there are exceptions to this as well.

Wind onset and withdrawal of Asian summer monsoon and their simulated performance in AMIP models

This study defines the concepts of wind onset and wind withdrawal to describe the abrupt seasonal variations of wind direction and circulation of the Asian monsoon. The patterns of wind onset and withdrawal show that the earliest wind onset in the tropical monsoon regions is found over equator around 70°–100°E and the southernmost South China Sea (SCS) and western Kalimantan, and the wind withdrawal shows a southward progression in tropics compared to the wind onset. A notable temporal boundary is found around 25°N in the subtropical western North Pacific (WNP), which may be related to the northward advance and southward retreat of the western Pacific subtropical high. The angle amplitudes of wind vectors in wind onset and withdrawal have distinct regional differences in Asian monsoon regions. Since the process of monsoon onset (withdrawal) may include several onsets of different variables without simultaneity, the relationships of the wind onset and withdrawal with the abrupt change of other variables (e.g. reversal of zonal wind, reversal of meridional wind, outgoing longwave radiation (OLR), precipitation) are investigated. The results indicate that the temporal discrepancies in different monsoon regions confirmed the asynchronous onsets. It also implies that the wind onset might be a good omen for monsoon precipitation in most regions since it is slightly earlier than rainy season onset. Seven Atmospheric Model Intercomparison Project (AMIP) models from Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are validated against observations mentioned above. Generally, the simulations of the multi-model ensemble mean are better than any individual model results. And the simulations of wind withdrawal are better than those of wind onset. For wind onset, IAP-FGOALS-1.0g, MIROC3.2 (medres) and MPI-ECHAM5 simulate reasonably well. For wind retreat, most models can capture the behaviors in tropics. However, there are still some discrepancies in a few models to simulate the dates of sudden change of monsoon wind direction. Moreover, most of models cannot reproduce the onset and withdrawal of both rainfall and OLR. The relationship between these discrepancies and the shortcomings of precipitation simulation is crucial for further investigating in the future.