Hadley Centre Coupled Model Version Research Articles

Evaluation of Climate Change Impacts on Run-Off in the Gidabo River Basin: Southern Ethiopia

Climate change meaningfully affects the runoff, flooding and the riverfow in Gidabo river basin. Thus, this research study deals with the climate change impacts on the runoff in the Gidabo River basin. Statistical Downscaling Model version 5.1 has been used to downscale the daily precipitation and temperature in the Gelana river basin. The output of HadCM3 coupled atmosphere-ocean GCM model for A2a and B2a scenarios obtained from the Hadley Centre Coupled Model version 3 were used to show future climate change. Climate change scenarios for precipitation and temperature were developed for three future periods: 2011–2040 (2050s), 2041–2070 (2050s) and 2071–2099 (2080s). The meteorological variables were used as input to the SWAT hydrological model which was calibrated (R2=0.77) and validated (R2=0.81) with meteorological and hydrological historical data from the year 1980-2006. The results obtained from this study indicate that there is significant variation in the monthly, seasonal and annual runoff. The climate change impacts might causes increases in average monthly runoff in the 2020’s, 2050’s and 2080’s for both A2a and B2a scenario. The result of this study is based on a single climate model (HadCM3) output under A2a and B2a scenarios. Therefore, multiple climate models and scenario which may provide a detail climate change impact studies for comparison on hydrology in the Gidabo river basin.

What Do Climate Change Projections Say About Future Droughts in Alabama and Georgia?

Abstract. Frequent severe droughts in recent years in the humid southeast U.S. have called for pragmatic approaches to better prepare for the consequences of droughts. This article examines how climate change will influence future droughts in Alabama and Georgia. Historic and future droughts were quantified by means of the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), and changes in the frequency, severity, and spatial extent of droughts were examined using severity-area-frequency (SAF) curves. Precipitation and temperature data, regionally downscaled using a regional spectral model (RSM) for the southeast U.S. for the high emission scenario (A2) from three general circulation models (GCM), i.e., Hadley Centre Coupled Model Version 3 (HadCM3), Geophysical Fluid Dynamics Laboratory (GFDL), and Community Climate System Model (CCSM), from the Third Coupled Model Inter-comparison Project (CMIP3) archive were used for this study. Data from 1969 to 1999 were used for historical simulation, and 2039 to 2069 were used for future projections. The results showed that droughts similar to those in the past would be observed frequently in the future as well. The SPI and SPEI from the GFDL and HadCM3 models indicated higher frequency, severity, and spatial extent of droughts in the future. The SPI from the CCSM model did not show drastic changes in drought characteristics in either of the two states. The results of this research can be used by policymakers as a guide to determine how drought characteristics are expected to change in the future, and to develop drought mitigation policies. Keywords: Climate change, Drought, Drought indices, Severity-area-frequency curves, Standardized precipitation index, Standardized precipitation evapotranspiration index.

Investigation of the snow-monsoon relationship in a warming atmosphere using Hadley Centre climate model

Several studies based on observed data and models show that there is an inverse relationship between the strength of the Indian summer monsoon and the extent/depth of Eurasian snow in the preceding season. Perturbed Physics Ensemble (PPE) simulations of Hadley Centre Coupled Model version 3 (HadCM3) have been used in this study to re-examine the snow-monsoon relationship in the longer time scale. The PPE monthly precipitation values during June, July, August and September (JJAS) have been compared with the corresponding values of Climatic Research Unit (CRU) of the University of East Anglia (UEA), UK for the period 1961–1990. The PPEs which simulated the Indian summer monsoon reasonably well have been used for examining snow-monsoon relationship. Atmospheric fields such as wind, geopotential height, velocity potential and stream function from the PPE simulations have been examined in detail. Results show that because of the west Eurasian snow depth anomalies, the mid-latitude circulation undergoes significant changes, which in turn lead to weak/strong monsoon circulation during deficient/excess Indian Summer Monsoon Rainfall (ISMR) respectively. The first Empirical Orthogonal Function (EOF1) of winter snow depth for the period 1961–1990 over the whole of Eurasia explains 13% variability. Thus the significant correlation patterns are consistent with the most dominant EOF of snow depth, in which the first mode describes a dipole type structure as observed. The study confirms that snow depth in the western part of Eurasia (20°E–65°E and 45°N–65°N) has negative correlation with the ISMR.

Performance Evaluation of a Developed Hybrid AOGCM Model under Climate Change

AbstractThe most comprehensive tools for producing climatic scenarios and consequently hydrological predictions are atmospheric-ocean general circulation models (AOGCMs). This paper evaluates the performance of those models. Possible scenarios of temperature and rainfall in the base period (1971–2000) for the Aidoghmoush basin located in East Azerbaijan are estimated with seven AOGCMs. A hydrological model is first calibrated for the basin and then monthly time series of temperature and rainfall resulting from AOGCMs in the base period are input to the hydrological model. The mean observed runoff (MOR) weighting method is employed to assess the effectiveness of each climate model to produce runoff. An appropriate probability distribution is chosen and relevant statistical parameters extracted and compared with observed runoff statistical parameters. Results show that the hybrid and Hadley Centre Coupled Model, version 3 (HadCM3) models with respective correlation coefficients of 97% [root mean square erro...

Future changes in rainfall, temperature and reference evapotranspiration in the central India by least square support vector machine

Climate change affects the environment and natural resources immensely. Rainfall, temperature and evapotranspiration are major parameters of climate affecting changes in the environment. Evapotranspiration plays a key role in crop production and water balance of a region, one of the major parameters affected by climate change. The reference evapotranspiration or ET0 is a calculated parameter used in this research. In the present study, changes in the future rainfall, minimum and maximum temperature, and ET0 have been shown by downscaling the HadCM3 (Hadley Centre Coupled Model version 3) model data. The selected study area is located in a part of the Narmada river basin area in Madhya Pradesh in central India. The downscaled outputs of projected rainfall, ET0 and temperatures have been shown for the 21st century with the HADCM3 data of A2 scenario by the Least Square Support Vector Machine (LS-SVM) model. The efficiency of the LS-SVM model was measured by different statistical methods. The selected predictors show considerable correlation with the rainfall and temperature and the application of this model has been done in a basin area which is an agriculture based region and is sensitive to the change of rainfall and temperature. Results showed an increase in the future rainfall, temperatures and ET0. The temperature increase is projected in the high rise of minimum temperature in winter time and the highest increase in maximum temperature is projected in the pre-monsoon season or from March to May. Highest increase is projected in the 2080s in 2081–2091 and 2091–2099 in maximum temperature and 2091–2099 in minimum temperature in all the stations. Winter maximum temperature has been observed to have increased in the future. High rainfall is also observed with higher ET0 in some decades. Two peaks of the increase are observed in ET0 in the April–May and in the October. Variation in these parameters due to climate change might have an impact on the future water resource of the study area, which is mainly an agricultural based region, and will help in proper planning and management.

Constructing the downscale precipitation using ANN model over the Kshipra river basin, Madhya Pradesh

The present study is focused on simulating the impact of climate change on the behavior of precipitationof Kshipra river basin in Madhya Pradesh, India.Artificial neural network (ANN) model was used to construct of the downscale precipitation scenario. A General Circulation Model (GCM) viz. Hadley Centre Coupled Model, version 3 (HadCM3), from Hadley Center, UK has been used for the study. In Model, monthly weather data on the basis of rapid economic growth under A1B scenario (A balanced emphasis on all energy sources) were considered. The four predictor variables which are used in ANN model formulation are screened from a set of 26 predictors based on correlation analysis of observed precipitation. The basic ANN architecture was optimized for training of the model byfirst selecting the training algorithm and then varying the number of neurons in the hidden layer. Twelve different training algorithms have been used. Further, the model was evaluated by varying the number of neurons from 1 to 30 in the hidden layer.The performance of modelwas evaluated in terms of the correlation coefficient (R), mean square error (MSE), root mean square error (RMSE) and mean absolute error (MAE). The results of model revealed that the predicted precipitation and observed precipitation are better correlated (R=0.911 and 0.853 during training and validation runs) with back propagation variable learning rate “traingdx” algorithm.

The biogeophysical climatic impacts of anthropogenic land use change during the Holocene

Abstract. The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June–July–August (JJA) season and throughout the entire annual cycle by 2–3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were −0.22 at 1850 CE, −0.11 at 2 ka BP, and −0.03 °C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of −0.83 at 1850 CE, −0.58 at 2 ka BP, and −0.24 °C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.

Vývoj potřeby závlahové vody v suchých oblastech České republiky s ohledem na možnou klimatickou změnu

The supposed climatic change in the Czech republic has be expressed with an increased occurence of unfavourable extreme phenomenons – floods and drought. This paper is dedicated to the agricultural drought. Irrigation is the most effective protection of crops against drought. The paper presents results of the calculations of the irrigation water requirements (for sprinkler irrigation) with the method of retrospective moisture balance (RVB) for representatives of main sorts of crops, i.e. cereals, technical crops, root-crops, fodder crops, vegetables (concretely perennial wheat, sugar-beet, new petatoes, alfaalfa, cucumbers) in the semiarid regions of the Czech republic (Southern Moravia, South-East Moravia, Middle Moravia, Žatecko and Lounsko, Litoměřicko, Middle Bohemia and Easter Bohemia) represented with 10 technical series (see tab. II) for recent years 1961 – 2000 and to the time horizons of years 2025, 2050 and 2075 with respect to a possible climatic change. The input meteorological data changes (average daily temperatures, daily precipitations and average daily air humidity) for calculations of irrigation water requirements to the introduced time horizons were realized by the help of the outputs of the scenarios for Bohemia and Moravia ascertained with the model of a climatic change HadCM3 (Hadley Centre Coupled Model, version 3). The results of the calculations for an average and a drought year (in tab. III) were the base for the determination of development trends of an irrigation water requirement for choosen crops to the year time horizons 2000, 2025, 2050, 2075. These trends were generally analysed for the all monitored semiarid regions of Bohemia and Moravia by means of regression straight lines (an example is shown in fig. 2). The results gained by means of the regress analysis are in tab. IV. They reflect the fact that the irrigation water requirement has an advancing development trend at all of chosen crops for an average and a dry year with an increase in a future time horizon. Simultaneously it is evident that values of the irrigation water requirements are in an average and a drought year for semiarid areas in Moravia, excepting insignificant exemptions, mostly bigger than these values for semiarid areas in Bohemia. The obtained results show, if irrigation will be expanded in the Czech republic, it´s necessary, by taking into an account all the time more accurate informations concerning the climatic change, to dedicate the permanent attention to the irrigation water requirements in semiarid areas of the Czech Republic, not only for separate crops but also for the whole cropping structures. The knowledge of the irrigation water requirements is an important base above all for the assesment of irrigation areas and the size of irrigation water resources.

Model to assess the impacts of external drivers on the hydrology of the Ganges River Basin

Abstract. Impact of climate change on the hydrology of the Ganges River Basin (GRB) is simulated by using a hydrological model – Soil and Water Assessment Tool (SWAT). Climate data from the GCM, Hadley Centre Coupled Model, version 3 (HadCM3) was downscaled with PRECIS for the GRB under A1B Special Report on Emission Scenarios (SRES) scenarios. The annual average precipitation will increase by 2.2% and 14.1% by 2030 and 2050, respectively, compared to the baseline period (1981–2010). Spatial distribution of the future precipitation shows that in the substantial areas of the middle part of the GRB, the annual precipitation in 2030 and 2050 will be reduced compared to the baseline period. Simulations indicate that in 2050 the total groundwater recharge would increase by 12%, while the increase of evapotranspiration will be about 10% compared to the baseline period. The water yield is also expected to increase in the future (up to 40% by 2050 compared to baseline), especially during the wetter months. The model setup is available for free from IWMI’s modelling inventory.

Responses of rice yield, irrigation water requirement and water use efficiency to climate change in China: Historical simulation and future projections

Rice is one of most important crops in China, accounting for approximately 18% of total cultivated area. Rice productivity is significantly affected by undergoing climate change and vulnerable with water stress. Therefore, investigating the responses of rice growth and water resources utilization to more pronounced climate change is of great importance for water resources planning and management in terms of maintaining the ecosystem integrity and ensuring the food security. In this study, the changes of rice yield, water consumption (ET), irrigation water requirement (IWR), water use efficiency (WUE) and irrigation water use efficiency (IWUE) from 1961 to 2010 in three typical sites (Kunshan and Nanjing in the Yangtze River Basin, and Kaifeng in the Yellow River Basin) in rice plantation region of China were evaluated by means of validated rice crop model ORYZA2000. Their responses to future climate scenarios of 21 century were investigated by driving ORYZA2000 with downscaling climatic data from HadCM3 (Hadley Centre Coupled Model version 3) under A2 and B2 emission scenarios with the help of a statistical downscaling method (SDSM). The results exhibit a significant decline in rice yield was identified by 49.3kgha−1, 32.0kgha−1 and 45.8kgha−1 for Kunshan station, Nanjing station and Kaifeng station, respectively, in the past 50 years due to obviously shortened rice growth duration (0.20daya−1, 0.15daya−1 and 0.27daya−1, respectively). While changes of ET and IWE were different for three stations representing by significant increase of ET and IWE in Kunshan, non-significant increase in Nanjing and significant decrease in Kaifeng. Whereas accompanying production reduction, simulated WUE and IWUE for three stations all presented significant deceasing trends ranging from 0.06kgha−1mm−1 to 0.16kgha−1mm−1. The future projection results under IPCC SRES A2 and B2 emission scenarios indicated the generally negative effect of climate warming to rice yield (maximum by −18.9% decline in 2090s in Kunshan) during the 21 century due to remarkable shortened growth period, resulting in generally depressed WUE and IWUE, although there would be the distinct response of the ET and IWR to future climate change for the three stations. Meanwhile, the increase of CO2 concentration under future climate is beneficial to raise the rice yield, alleviate crop water consumption and irrigation water requirements and improve the water use efficiencies of rice in a certain degree. Further works should be carried out to capture simulation uncertainties in climate change impact assessment with consideration of interactions among anthropogenic activities, environmental and biological factors.

Climate‐Induced Flow Regime Alterations and their Implications for the Lancang River, China

AbstractMost studies of the Lancang River have focussed on the influence of hydropower generation on the riverine ecosystem. Few studies have explored climate‐induced flow regime alterations and their implications for the riverine ecosystem. There is a pressing need for improved understanding of the implications of such climate‐induced flow regime alterations in the Lancang River Basin. Future streamflow under the A2 and B2 scenarios of Hadley Centre coupled model version 3 (HadCM3) are predicted using a back propagation artificial neural network. Potential effects of flow regime alterations are tested by amended annual proportional flow deviation (AAPFD). Projected streamflow will decrease in wet season months and will increase in dry season months. Monthly streamflow at Jiuzhou station was projected to range from a 27.9% decrease to a 158.4% increase. For Gajiu station, the percent increase was projected to range from 1.4% to 70.4%, while the decrease ranged from 0.2% to 16.9%. Changes in streamflow at Yunjinghong station ranged from a 46.5% decrease to a 135.3% increase. Projected streamflow changes during high and low flow periods will have important implications for the ecological processes of the Lancang River Basin. AAPFD indicates that these changes will have serious effects on the Lancang River Basin ecosystem. Projected climate‐induced flow regime alterations during the period of 2071–2095 will have particularly serious effects on riverine ecosystem, especially in the upstream and downstream sections of the Lancang River. The A2 scenario will pose a more serious threat to riverine ecosystem health. Copyright © 2014 John Wiley & Sons, Ltd.

High-Resolution Climate Change Impact Analysis on Expected Future Water Availability in the Upper Jordan Catchment and the Middle East

Abstract The impact of climate change on the future water availability of the upper Jordan River (UJR) and its tributaries Dan, Snir, and Hermon located in the eastern Mediterranean is evaluated by a highly resolved distributed approach with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) run at 18.6- and 6.2-km resolution offline coupled with the Water Flow and Balance Simulation Model (WaSiM). The MM5 was driven with NCEP reanalysis for 1971–2000 and with Hadley Centre Coupled Model, version 3 (HadCM3), GCM forcings for 1971–2099. Because only one regional–global climate model combination was applied, the results may not give the full range of possible future projections. To describe the Dan spring behavior, the hydrological model was extended by a bypass approach to allow the fast discharge components of the Snir to enter the Dan catchment. Simulation results for the period 1976–2000 reveal that the coupled system was able to reproduce the observed discharge rates in the partially karstic complex terrain to a reasonable extent with the high-resolution 6.2-km meteorological input only. The performed future climate simulations show steadily rising temperatures with 2.2 K above the 1976–2000 mean for the period 2031–60 and 3.5 K for the period 2070–99. Precipitation trends are insignificant until the middle of the century, although a decrease of approximately 12% is simulated. For the end of the century, a reduction in rainfall ranging between 10% and 35% can be expected. Discharge in the UJR is simulated to decrease by 12% until 2060 and by 26% until 2099, both related to the 1976–2000 mean. The discharge decrease is associated with a lower number of high river flow years.

State of the tropical Pacific Ocean and its enhanced impact on precipitation over East Asia during marine isotopic stage 13

Multiple terrestrial records suggest that marine isotopic stage 13 (MIS-13), an interglacial period approximately 0.5 million years ago, had the strongest East Asian summer monsoon (EASM) of the last one million years. This is unexpected given that, compared to other interglacials, MIS-13 was globally cooler with a lower CO2 concentration. We use two coupled atmosphere–ocean general circulation models, the Hadley Centre Coupled Model, version 3 (HadCM3) and Community Climate System Model, version 3.0 (CCSM3), to simulate the climate of MIS-13 forced with different insolation and greenhouse gas concentrations relative to the pre-industrial (PrI) situation. Both models confirm a stronger EASM during MIS-13 compared to PrI. Here we specially focus on analyzing the impact of the tropical Pacific Ocean on the EASM. Our simulations suggest that the mean climatic state in the tropical Pacific during MIS-13 was La Nina-like and thatassociated teleconnections with the extra-tropics favored increased precipitation over the EASM. As compared to PrI, it is found that the summer (June–July–August) sea surface temperature (SST) is warmer in the eastern tropical Pacific Ocean and colder to the west. In concert with previous studies, we show that colder summer SSTs in the central tropical Pacific during MIS-13 promotes an upperlevel teleconnection between the tropical Pacific Ocean and EASM. It also contributes to the strengthening of the northern Pacific subtropical high and, therefore, the transport of more moisture into the EASM. We suggest that the reduced east–west SST difference in the tropical Pacific in summer helps to maintain the teleconnection between the tropical Pacific and EASM. The correlation between tropical Pacific SSTs and the EASM was higher in our MIS-13 simulations, further supporting the enhancement of their relationship. It is found that the pure impact of El Nino Southern Oscillation on EASM precipitation increases by up to 30 % in MIS-13 for HadCM3 while it is minor for CCSM3. Better constraining the spatio-temporal variability of tropical Pacific SST during the interglacials may thus help explain the anomalously strong EASM during MIS-13 which has been observed from geological records.

Key factors governing uncertainty in the response to sunshade geoengineering from a comparison of the GeoMIP ensemble and a perturbed parameter ensemble

Climate model studies of the consequences of solar geoengineering are central to evaluating whether such approaches may help to reduce the harmful impacts of global warming. In this study we compare the sunshade solar geoengineering response of a perturbed parameter ensemble (PPE) of the Hadley Centre Coupled Model version 3 (HadCM3) with a multimodel ensemble (MME) by analyzing the G1 experiment from the Geoengineering Model Intercomparison Project (GeoMIP). The PPE only perturbed a small number of parameters and shares a common structure with the unperturbed HadCM3 model, and so the additional weight the PPE adds to the robustness of the common climate response features in the MME is minor. However, analysis of the PPE indicates some of the factors that drive the spread within the MME. We isolate the role of global mean temperature biases for both ensembles and find that these biases have little effect on the ensemble spread in the hydrological response but do reduce the spread in surface air temperature response, particularly at high latitudes. We investigate the role of the preindustrial climatology and find that biases here are likely a key source of ensemble spread at the zonal and grid cell level. The role of vegetation, and its response to elevated CO2 concentrations through the CO2 physiological effect and changes in plant productivity, is also investigated and proves to have a substantial effect on the terrestrial hydrological response to solar geoengineering and to be a major source of variation within the GeoMIP ensemble.

Predicting climate change effects on surface soil organic carbon of Louisiana, USA.

This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5° × 0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001-2010, 2041-2050, and 2091-2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer (p < 0.01) adjusted means into letter comparisons. The study found that for most of the next 100 years in Louisiana, monthly mean temperature under all three emissions projections will increase; and monthly precipitation will, however, decrease. Under three emission scenarios, A1FI, A2, and B2, the mean SOC in the upper 30-cm depth of Louisiana forest soils will decrease from 33.0 t/ha in 2001 to 26.9, 28.4, and 29.2 t/ha in 2100, respectively; the mean SOC of Louisiana cropland soils will decrease from 44.4 t/ha in 2001 to 36.3, 38.4, and 39.6 t/ha in 2100, respectively; the mean SOC of Louisiana grassland soils will change from 30.7 t/ha in 2001 to 25.4, 26.6, and 27.0 t/ha in 2100, respectively. Annual SOC changes will be significantly different among the land cover classes including evergreen forest, mixed forest, deciduous forest, small grains, row crops, and pasture/hay (p < 0.0001), emissions scenarios (p < 0.0001), and their interactions (p < 0.0001).

Assessing orbitally-forced interglacial climate variability during the mid-Pliocene Warm Period

The traditional view of the Pliocene is one of an epoch with higher than present global mean annual temperatures (∼2 to 3 °C) and stable climate conditions. Published data-model comparisons for the mid-Pliocene Warm Period (mPWP: ∼3.3 to 3 million years ago) have identified specific regions of concordance and discord between climate model outputs and marine/terrestrial proxy data. Due to the time averaged nature of global palaeoenvironmental syntheses, it has been hypothesised that climate variability during interglacial events within the mPWP could contribute to site-specific data/model disagreement. The Hadley Centre Coupled Climate Model Version 3 (HadCM3) is used to assess the nature of climate variability around two interglacial events within the mPWP that have different characteristics of orbital forcing (Marine Isotope Stages KM5c and K1). Model results indicate that ±20 kyr on either side of the MIS KM5c, orbital forcing produced a less than 1 °C change in global mean annual temperatures. Regionally, mean annual surface air temperature (SAT) variability can reach 2 to 3 °C. Seasonal variations exceed those predicted for the annual mean and can locally exceed 5 °C. Simulations 20 kyr on either side of MIS K1 show considerably increased variability in relation to KM5c.We demonstrate that orbitally-forced changes in surface air temperature during interglacial events within the mPWP can be substantial, and could therefore contribute to data/model discord. This is especially likely if proxies preserve growing season rather than mean annual temperatures.Model results indicate that peak MIS KM5c and K1 interglacial temperatures were not globally synchronous, highlighting leads and lags in temperature in different regions. This highlights the potential pitfalls in aligning peaks in proxy-derived temperatures across geographically diverse data sites, and indicates that a single climate model simulation for an interglacial event is inadequate to capture peak temperature change in all regions.We conclude that the premise of sustained global warmth and stable Pliocene climate conditions is incomplete. We also contend that the likely nature of Pliocene interglacial climate variability is more akin to interglacial events within the Quaternary, where the character of interglacials is known to be diverse. In the future, the utility of Pliocene data/model comparisons is dependent upon 1) establishing precise chronology of the proxy data, 2) providing climate models with fully proxy-consistent boundary conditions and 3) in utilising ensembles of climate simulations that can adequately capture orbital variability around any studied interval.

Adaptation strategies for rice cultivation under climate change in Central Vietnam

This study investigates the impact of climate change on winter and summer rice (Oryza sativa) yield and evaluates several adaptation measures to overcome the negative impact of climate change on rice production in the Quang Nam province of Vietnam. Future climate change scenarios for time periods in the 2020s, 2050s and 2080s were projected by downscaling the outputs of the General Circulation Model (GCM), Hadley Centre Coupled Model, version 3 (HadCM3) A2 and B2 scenarios. The AquaCrop model was used to simulate the impact of future climates on rice yield. The minimum and maximum temperature of the province is projected to increase by 0.35–1.72 °C and 0.93–3.69 °C respectively in future. Similarly, the annual precipitation is expected to increase by 9.75 % in the 2080s. Results show that climate change will reduce rice yield from 1.29 to 23.05 % during the winter season for both scenarios and all time periods, whereas an increase in yield by 2.07 to 6.66 % is expected in the summer season for the 2020s and 2050s; relative to baseline yield. The overall decrease of rice yield in the winter season can be offset, and rice yield in the summer season can be enhanced to potential levels by altering the transplanting dates and by introducing supplementary irrigation. Late transplanting of rice shows an increase of yield by 20–27 % in future. Whereas supplementary irrigation of rice in the winter season shows an increase in yield of up to 42 % in future. Increasing the fertilizer application rate enhances the yield from 0.3 to 29.8 % under future climates. Similarly, changing the number of doses of fertilizer application increased rice yield by 1.8 to 5.1 %, relative to the current practice of single dose application. Shifting to other heat tolerant varieties also increased the rice production. Based on the findings, changing planting dates, supplementary irrigation, proper nutrient management and adopting to new rice cultivars can be beneficial for the adaptation of rice cultivation under climate change scenarios in central Vietnam.

Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071–2099) and the base period (1961–1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and hydrological simulations and development of agricultural and hydrological models.

The Interpretation and Use of Biases in Decadal Climate Predictions

Abstract Decadal climate predictions exhibit large biases, which are often subtracted and forgotten. However, understanding the causes of bias is essential to guide efforts to improve prediction systems, and may offer additional benefits. Here the origins of biases in decadal predictions are investigated, including whether analysis of these biases might provide useful information. The focus is especially on the lead-time-dependent bias tendency. A “toy” model of a prediction system is initially developed and used to show that there are several distinct contributions to bias tendency. Contributions from sampling of internal variability and a start-time-dependent forcing bias can be estimated and removed to obtain a much improved estimate of the true bias tendency, which can provide information about errors in the underlying model and/or errors in the specification of forcings. It is argued that the true bias tendency, not the total bias tendency, should be used to adjust decadal forecasts. The methods developed are applied to decadal hindcasts of global mean temperature made using the Hadley Centre Coupled Model, version 3 (HadCM3), climate model, and it is found that this model exhibits a small positive bias tendency in the ensemble mean. When considering different model versions, it is shown that the true bias tendency is very highly correlated with both the transient climate response (TCR) and non–greenhouse gas forcing trends, and can therefore be used to obtain observationally constrained estimates of these relevant physical quantities.

Future potential evapotranspiration changes and contribution analysis in Zhejiang Province, East China

AbstractPotential evapotranspiration is an important component of hydrological modeling. In this study, the objective is to project potential evapotranspiration in the future period 2011–2040 and understand their changes in Zhejiang Province, East China. The sensitivity of potential evapotranspiration to five climatic variables (solar radiation, daily minimum and maximum air temperature, relative humidity, and wind speed) is analyzed based on observation data from 1955–2008 using a global sensitivity analysis method, Sobol's method. The changes in potential evapotranspiration during the future period are generated using one regional climate model, Providing Regional Climates for Impacts Studies, with two global climate models, ECHAM5 and Hadley Centre Coupled Model version 3, and their causes are analyzed based on sensitivity analysis results. Global sensitivity analysis results reveal substantial spatial‐temporal variations in the sensitivity of potential evapotranspiration to climatic variables and unignorable interactions among climatic variables. Rather similar spatial change patterns of annual mean potential evapotranspiration (PET) are generated for both general circulation models; however, seasonal or monthly changes are very different due to different spatial‐temporal changes in climatic variables. Different contributory sources to potential evapotranspiration changes are identified at different months and stations; the PET changes in 2011–2040 are mainly due to three climatic variables including solar radiation, relative humidity, and daily minimum temperature.