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The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., 'idealized but realistic' forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the twentieth century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60 % of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40 % of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought. [ABSTRACT FROM AUTHOR]

This paper investigates the potential impact of 'idealized-but-realistic' land cover degradation on the late twentieth century Sahel drought using a regional climate model (RCM) driven with lateral boundary conditions (LBCs) from three different sources, including one re-analysis data and two global climate models (GCMs). The impact of land cover degradation is quantified based on a large number of control-and-experiment pairs of simulations, where the experiment features a degraded land cover relative to the control. Two different approaches of experimental design are tested: in the 1st approach, the RCM land cover degradation experiment shares the same LBCs as the corresponding RCM control, which can be derived from either reanalysis data or a GCM; with the 2nd approach, the LBCs for the RCM control are derived from a GCM control, and the LBCs for the RCM land cover degradation experiment are derived from a corresponding GCM land cover degradation experiment. When the 1st approach is used, results from the RCM driven with the three different sources of LBCs are generally consistent with each other, indicating robustness of the model response against LBCs; when the 2nd approach is used, the RCM results show strong sensitivity to the source of LBCs and the response in the RCM is dominated by the response of the driving GCMs. The spatiotemporal pattern of the precipitation response to land cover degradation as simulated by RCM using the 1st approach closely resembles that of the observed historical changes, while results from the GCMs and the RCM using the 2nd approach bear less similarity to observations. Compared with the 1st approach, the 2nd approach has the advantage of capturing the impact on large scale circulation, but has the disadvantage of being influenced by the GCMs' internal variability and any potential erroneous response of the driving GCMs to land degradation. The 2nd approach therefore requires a large ensemble to reduce the uncertainties derived from the driving GCMs. All RCM experiments based on the 1st approach produce a predominantly dry signal in West Africa throughout the year, with a dipole pattern found in the peak monsoon season that features a slight increase of precipitation over the Guinea Coast and strong decrease in the north; a similar spatiotemporal distribution is found for temperature changes, with warming (cooling) coinciding with precipitation decrease (increase). The model precipitation changes in West Africa are dominated by evapotranspiration changes in the north and by atmospheric moisture convergence changes in the south; in temperature changes, surface warming due to the decrease of evaporative cooling dominates over the albedo-induced radiative cooling. [ABSTRACT FROM AUTHOR]

The West African monsoon intraseasonal variability has huge socio-economic impacts on local populations but understanding and predicting it still remains a challenge for the weather prediction and climate scientific community. This paper analyses an ensemble of simulations from six regional climate models (RCMs) taking part in the coordinated regional downscaling experiment, the ECMWF ERA-Interim reanalysis (ERAI) and three satellite-based and observationally-constrained daily precipitation datasets, to assess the performance of the RCMs with regard to the intraseasonal variability. A joint analysis of seasonal-mean precipitation and the total column water vapor (also called precipitable water- PW) suggests the existence of important links at different timescales between these two variables over the Sahel and highlights the relevance of using PW to follow the monsoon seasonal cycle. RCMs that fail to represent the seasonal-mean position and amplitude of the meridional gradient of PW show the largest discrepancies with respect to seasonal-mean observed precipitation. For both ERAI and RCMs, spectral decompositions of daily PW as well as rainfall show an overestimation of low-frequency activity (at timescales longer than 10 days) at the expense of the synoptic (timescales shorter than 10 days) activity. Consequently, the effects of the African Easterly Waves and the associated mesoscale convective systems are substantially underestimated, especially over continental regions. Finally, the study investigates the skill of the models with respect to hydro-climatic indices related to the occurrence, intensity and frequency of precipitation events at the intraseasonal scale. Although most of these indices are generally better reproduced with RCMs than reanalysis products, this study indicates that RCMs still need to be improved (especially with respect to their subgrid-scale parameterization schemes) to be able to reproduce the intraseasonal variance spectrum adequately. [ABSTRACT FROM AUTHOR]

Convection-permitting climate model are promising tools for improved representation of extremes, but the number of regions for which these models have been evaluated are still rather limited to make robust conclusions. In addition, an integrated interpretation of near-surface characteristics (typically temperature and precipitation) together with cloud properties is limited. The objective of this paper is to comprehensively evaluate the performance of a 'state-of-the-art' regional convection-permitting climate model for a mid-latitude coastal region with little orographic forcing. For this purpose, an 11-year integration with the COSMO-CLM model at Convection-Permitting Scale (CPS) using a grid spacing of 2.8 km was compared with in-situ and satellite-based observations of precipitation, temperature, cloud properties and radiation (both at the surface and the top of the atmosphere). CPS clearly improves the representation of precipitation, in especially the diurnal cycle, intensity and spatial distribution of hourly precipitation. Improvements in the representation of temperature are less obvious. In fact the CPS integration overestimates both low and high temperature extremes. The underlying cause for the overestimation of high temperature extremes was attributed to deficiencies in the cloud properties: The modelled cloud fraction is only 46 % whereas a cloud fraction of 65 % was observed. Surprisingly, the effect of this deficiency was less pronounced at the radiation balance at the top of the atmosphere due to a compensating error, in particular an overestimation of the reflectivity of clouds when they are present. Overall, a better representation of convective precipitation and a very good representation of the daily cycle in different cloud types were demonstrated. However, to overcome remaining deficiencies, additional efforts are necessary to improve cloud characteristics in CPS. This will be a challenging task due to compensating deficiencies that currently exist in 'state-of-the-art' models, yielding a good representation of average climate conditions. In the light of using the CPS models to study climate change it is necessary that these deficiencies are addressed in future research. [ABSTRACT FROM AUTHOR]

This paper provides a first overview of the performance of global climate models participating in the Coupled Model Inter-Comparison Project phase 5 (CMIP5) in simulating the upper troposphere and lower stratosphere (UTLS) temperatures. Temperature from CMIP5 models is evaluated with high resolution global positioning system radio occultation (GPSRO) constellation observing system for meteorology, ionosphere, and climate (COSMIC) data during the period of July 2006-December 2013. Future projections of 17 CMIP5 models based on the representative concentration pathway (RCP) 8.5 scenarios are utilized to assess model performance and to identify the biases in the temperature in the UTLS region at eight different pressure levels. The evaluations were carried out vertically, regionally, and globally to understand the temperature uncertainties in CMIP5 models. It is found that the CMIP5 models successfully reproduce the general features of temperature structure in terms of vertical, annual, and inter-annual variation. The ensemble mean of CMIP5 models compares well with the COSMIC GPSRO data with a mean difference of ±1 K. In the tropical region, temperature biases vary from one model to another. The spatial difference between COSMIC and ensemble mean reveals that at 100 hPa, the models show a bias of about ±2 K. With increase in altitude the bias decreases and turns into a cold bias over the tropical and Antarctic regions. The future projections of the CMIP5 models were presented during 2006-2099 under the RCP 8.5 scenarios. Projections show a warming trend at 300, 200, and 100 hPa levels over a wide region of 60°N-45°S. The warming decreases rapidly and becomes cooling with increase in altitudes by the end of twenty-first century. Significant cooling is observed at 30, 20, and 10 hPa levels. At 300/10 hPa, the temperature trend increases/decreases by ~0.82/0.88 K/decade at the end of twenty-first century under RCP 8.5 scenarios. [ABSTRACT FROM AUTHOR]

The eastern United States is vulnerable to flooding from tropical cyclone rainfall. Understanding how both the frequency and intensity of this rainfall will change in the future climate is a major challenge. One promising approach is the dynamical downscaling of relatively coarse general circulation model results using higher-resolution regional climate models (RCMs). In this paper, we examine the frequency of landfalling tropical cyclones and associated rainfall properties over the eastern United States using Zetac, an 18-km resolution RCM designed for modeling Atlantic tropical cyclone activity. Simulations of 1980-2006 tropical cyclone frequency and rainfall intensity for the months of August-October are compared against results from previous studies and observation-based datasets. The 1980-2006 control simulations are then compared against results from three future climate scenarios: CMIP3/A1B (late twenty-first century) and CMIP5/RCP4.5 (early and late twenty-first century). In CMIP5 early and late twenty-first century projections, the frequency of occurrence of post-landfall tropical cyclones shows little net change over much of the eastern U.S. despite a decrease in frequency over the ocean. This reflects a greater landfalling fraction in CMIP5 projections, which is not seen in CMIP3-based projections. Average tropical cyclone rain rates over land within 500 km of the storm center increase by 8-17 % in the future climate projections relative to control. This is at least as much as expected from the Clausius-Clapeyron relation, which links a warmer atmosphere to greater atmospheric water vapor content. Over land, the percent enhancement of area-averaged rain rates from a given tropical cyclone in the warmer climate is greater for larger averaging radius (300-500 km) than near the storm, particularly for the CMIP3 projections. Although this study does not focus on attribution, the findings are broadly consistent with historical tropical cyclone rainfall changes documented in a recent observational study. The results may have important implications for future flood risks from tropical cyclones. [ABSTRACT FROM AUTHOR]

This paper analyzes the ability of the multi-model simulations from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) to simulate the main leading modes of variability over the Euro-Atlantic region in winter: the North-Atlantic Oscillation (NAO), the Scandinavian mode (SCAND), the East/Atlantic Oscillation (EA) and the East Atlantic/Western Russia mode (EA/WR). These modes of variability have been evaluated both spatially, by analyzing the intensity and location of their anomaly centres, as well as temporally, by focusing on the probability density functions and e-folding time scales. The choice of variability modes as a tool for climate model assessment can be justified by the fact that modes of variability determine local climatic conditions and their likely change may have important implications for future climate changes. It is found that all the models considered are able to simulate reasonably well these four variability modes, the SCAND being the mode which is best spatially simulated. From a temporal point of view the NAO and SCAND modes are the best simulated. UKMO-HadGEM1 and CGCM3.1(T63) are the models best at reproducing spatial characteristics, whereas CCSM3 and CGCM3.1(T63) are the best ones with regard to the temporal features. GISS-AOM is the model showing the worst performance, in terms of both spatial and temporal features. These results may bring new insight into the selection and use of specific models to simulate Euro-Atlantic climate, with some models being clearly more successful in simulating patterns of temporal and spatial variability than others. [ABSTRACT FROM AUTHOR]

The North Atlantic Oscillation (NAO) is the dominant mode of winter climate variability in the North Atlantic sector. The corresponding index varies on a wide range of timescales, from days and months to decades and beyond. Sub-decadal NAO variability has been well documented, but the underlying mechanism is still under discussion. Other indices of North Atlantic sector climate variability such as indices of sea surface and surface air temperature or Arctic sea ice extent also exhibit pronounced sub-decadal variability. Here, we use sea surface temperature and sea level pressure observations, and the Kiel Climate Model to investigate the dynamics of the sub-decadal NAO variability. The sub-decadal NAO variability is suggested to originate from dynamical large-scale air-sea interactions. The adjustment of the Atlantic Meridional Overturning Circulation to previous surface heat flux variability provides the memory of the coupled mode. The results stress the role of coupled feedbacks in generating sub-decadal North Atlantic sector climate variability, which is important to multiyear climate predictability in that region. [ABSTRACT FROM AUTHOR]

The El Niño/Southern Oscillation (ENSO) is the leading mode of tropical Pacific interannual variability in the present-day climate. Available proxy evidence suggests that ENSO also existed during past climates, for example during the Pliocene extending from about 5.3 million to about 2.6 million years BP. Here we investigate the influences of the Panama Seaway closing and Indonesian Passages narrowing, and also of atmospheric carbon dioxide (CO) on the tropical Pacific mean climate and annual cycle, and their combined impact on ENSO during the Pliocene. To this end the Kiel Climate Model), a global climate model, is employed to study the influences of the changing geometry and CO-concentration. We find that ENSO is sensitive to the closing of the Panama Seaway, with ENSO amplitude being reduced by about 15-20 %. The narrowing of the Indonesian Passages enhances ENSO strength but only by about 6 %. ENSO period changes are modest and the spectral ENSO peak stays rather broad. Annual cycle changes are more prominent. An intensification of the annual cycle by about 50 % is simulated in response to the closing of the Panama Seaway, which is largely attributed to the strengthening of meridional wind stress. In comparison to the closing of the Panama Seaway, the narrowing of the Indonesian Passages only drives relatively weak changes in the annual cycle. A robust relationship is found such that ENSO amplitude strengthens when the annual cycle amplitude weakens. [ABSTRACT FROM AUTHOR]

Surface-based Arctic amplification (AA) has experienced a remarkable increase in recent decades. Therefore, it is important to understand how Arctic warming might change in response to global warming. By analyzing the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model dataset, we examine how AA correlates with changes in tropical Pacific precipitation in response to global warming. It is found that that the changes in the latitudinal position of the Inter-tropical Convergence Zone (ITCZ) are associated to the simulated AA strength in the CMIP5 climate models. Specifically, AA tends to be stronger (weaker) in models where the ITCZ shifts relatively more northward (southward). Further analysis indicates that the inter-model diversity of AA strength in the CMIP5 climate models is related to the changes in large-scale atmospheric circulation associated with the meridional shift of the ITCZ. These results emphasize a close relationship between AA and changes in tropical Pacific precipitation in response to global warming. [ABSTRACT FROM AUTHOR]

We use the output of twenty-seven Global Climate Models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5) to investigate the temperature changes and their dependence on the elevation in the Tibetan Plateau, Himalaya and Karakoram mountains and in the surrounding areas in historical model simulations and in future projections. The aim of this study is to explore if and to what extent the CMIP5 models show elevation-dependent warming (EDW) in this part of the globe and to investigate what are the driving factors at play and their relative importance. Our results indicate that the models show enhanced rates of warming at higher elevations in the Tibetan Plateau-Himalayan region in the twentieth century, and this phenomenon is projected to strengthen by the end of the twenty-first century under a high-emission scenario. We find a nonlinear relationship between the warming rates and the elevation, for both the minimum and the maximum temperature: regions with temperatures below the freezing level of water show more warming than the regions with temperatures above, likely suggesting a key role of mechanisms involving water phase changes, the presence/absence of snow and the snow-albedo feedback. We consider the main variables simulated by the CMIP5 models whose change may be related to temperature changes at higher elevations. We find that changes in surface albedo, atmospheric humidity and downward longwave radiation are relevant factors for EDW in the Tibetan Plateau-Himalayas, with surface albedo being the leading driver. [ABSTRACT FROM AUTHOR]

The key role of the South Atlantic Anticyclone (SAA) on the seasonal cycle of the tropical Atlantic is investigated with a regionally coupled atmosphere-ocean model for two different coupled domains. Both domains include the equatorial Atlantic and a large portion of the northern tropical Atlantic, but one extends southward, and the other northwestward. The SAA is simulated as internal model variability in the former, and is prescribed as external forcing in the latter. In the first case, the model shows significant warm biases in sea surface temperature (SST) in the Angola-Benguela front zone. If the SAA is externally prescribed, these biases are substantially reduced. The biases are both of oceanic and atmospheric origin, and are influenced by ocean-atmosphere interactions in coupled runs. The strong SST austral summer biases are associated with a weaker SAA, which weakens the winds over the southeastern tropical Atlantic, deepens the thermocline and prevents the local coastal upwelling of colder water. The biases in the basins interior in this season could be related to the advection and eddy transport of the coastal warm anomalies. In winter, the deeper thermocline and atmospheric fluxes are probably the main biases sources. Biases in incoming solar radiation and thus cloudiness seem to be a secondary effect only observed in austral winter. We conclude that the external prescription of the SAA south of 20°S improves the simulation of the seasonal cycle over the tropical Atlantic, revealing the fundamental role of this anticyclone in shaping the climate over this region. [ABSTRACT FROM AUTHOR]

The hard snowball Earth bifurcation point is determined by the level of atmospheric carbon dioxide concentration ( pCO) below which complete glaciation of the planet would occur. In previous studies, the bifurcation point was determined based on the assumption that the extent of continental glaciation could be neglected and the results thereby obtained suggested that very low values of pCO would be required (~100 ppmv). Here, we deduce the upper bound on the bifurcation point using the coupled atmosphere-ocean climate model of the NCAR that is referred to as the Community Climate System Model version 3 by assuming that the continents are fully covered by ice sheets prior to executing the transition into the hard snowball state. The thickness of the ice sheet is assumed to be that obtained by an ice-sheet model coupled to an energy balance model for a soft snowball Earth. We find that the hard snowball Earth bifurcation point is in the ranges of 600-630 and 300-320 ppmv for the 720 and 570 Ma continental configurations, respectively. These critical points are between 10 and 3 times higher than their respective values when ice sheets are completely neglected. We also find that when the ice sheets are thinner than those assumed above, the climate is colder and the bifurcation point is larger. The key process that causes the excess cooling when continental ice sheets are thin is shown to be associated with the fact that atmospheric heat transport from the adjacent oceans to the ice sheet-covered continents is enhanced in such conditions. Feedbacks from sea-ice expansion and reduced water vapor concentration further cool the oceanic regions strongly. [ABSTRACT FROM AUTHOR]

This study assesses projected changes to drought characteristics in Alberta, Saskatchewan and Manitoba, the prairie provinces of Canada, using a multi-regional climate model (RCM) ensemble available through the North American Regional Climate Change Assessment Program. Simulations considered include those performed with six RCMs driven by National Center for Environmental Prediction reanalysis II for the 1981-2003 period and those driven by four Atmosphere-Ocean General Circulation Models for the 1970-1999 and 2041-2070 periods (i.e. eleven current and the same number of corresponding future period simulations). Drought characteristics are extracted using two drought indices, namely the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Regional frequency analysis is used to project changes to selected 20- and 50-year regional return levels of drought characteristics for fifteen homogeneous regions, covering the study area. In addition, multivariate analyses of drought characteristics, derived on the basis of 6-month SPI and SPEI values, are developed using the copula approach for each region. Analysis of multi-RCM ensemble-averaged projected changes to mean and selected return levels of drought characteristics show increases over the southern and south-western parts of the study area. Based on bi- and trivariate joint occurrence probabilities of drought characteristics, the southern regions along with the central regions are found highly drought vulnerable, followed by the southwestern and southeastern regions. Compared to the SPI-based analysis, the results based on SPEI suggest drier conditions over many regions in the future, indicating potential effects of rising temperatures on drought risks. These projections will be useful in the development of appropriate adaptation strategies for the water and agricultural sectors, which play an important role in the economy of the study area. [ABSTRACT FROM AUTHOR]

Commonly termed 'added value', the additional regional details gained by high-resolution regional climate models (RCMs) over the coarser resolution reanalysis driving data are often indistinguishable at the 0.44° grid mesh computationally affordable large CORDEX domains. In an attempt to highlight the benefits of finer resolutions to study the RCM added value, five North American weather phenomena are evaluated in RCM hindcast simulations using grid meshes of 0.44°, 0.22° and 0.11° with available observations. The results show that the orographic precipitation on the west coast of North America is enhanced and more realistic, with two distinct rain bands in the finer resolution simulation. The spatial distribution of precipitation in August and the high frequency of summer precipitation extremes over southwestern United States reveal that the North American monsoon is improved with increasing resolution. Only the finer RCM simulation shows skill at producing snowbelts around the Great Lakes by capturing lake-effect snow. A comparison of wind roses in the St. Lawrence River Valley indicates that only the finer RCM simulation is able to reproduce wind channeling by resolving complex orography. Finally, the simulation of the summer land-sea breezes by the RCM simulations leads to added value in the diurnal cycle of precipitation over the Florida peninsula and the Caribbean islands. Overall, the almost systematic improvements of the finer resolution simulations suggest that higher resolutions, only computationally affordable over smaller domains, might get a higher priority to promote RCM added value. [ABSTRACT FROM AUTHOR]

The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June-September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2° latitude by 2.5° longitude and the RM3 grid spacing is 0.44°. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases. [ABSTRACT FROM AUTHOR]

At decadal time scales, the capability of state-of-the-art atmosphere-ocean coupled climate models in predicting the precipitation in Sahel is assessed. A set of 14 models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) is selected and two experiments are analysed, namely initialized decadal hindcasts and forced historical simulations. Considering the strong linkage of the atmospheric circulation signatures over West Africa with the rainfall variability, this study aims to investigate the potential of using wind fields for decadal predictions. Namely, a West African monsoon index (WAMI) is defined, based on the coherence of low (925 hPa) and high (200 hPa) troposphere wind fields, which accounts for the intensity of the monsoonal circulation. A combined empirical orthogonal functions analysis is applied to explore the wind fields' covariance modes, and a set of indices is defined on the basis of the identified patterns. The WAMI predictive skill is assessed by comparing WAMI from coupled models with WAMI from reanalysis products and with a standardized precipitation index (SPI) from observations. Results suggest that the predictive skill is highly model dependent and it is strongly related to the WAMI definition. In addition, hindcasts are more skilful than historical simulations in both deterministic and probability forecasts, which suggests an added value of initialization for decadal predictability. Moreover, coupled models are more skilful in predicting the observed SPI than the WAMI obtained from reanalysis. WAMI performance is also compared with decadal predictions from CMIP5 models based on a Sahelian precipitation index, and an improvement in predictive skill is observed in some models when WAMI is used. Therefore, we conclude that dynamics-based indices are potentially more effective for decadal prediction of precipitation in Sahel than precipitation-based indices for those models in which Sahel rainfall variability is not well simulated. We thus recommend a two-fold approach when testing the performance of models in predicting Sahel rainfall, based not only on rainfall but also on the dynamics of the West African monsoon. [ABSTRACT FROM AUTHOR]

The population of the Sahel region of West Africa has approximately doubled in the past 50 years, and could potentially double again by the middle of this century. This has led to the northward expansion of agricultural areas at the expense of natural savanna, leading to widespread land use -land cover change (LULCC). Because there is strong evidence of significant surface-atmosphere coupling in this region, one of the main goals of the West African Monsoon Modeling and Evaluation project phase II is to provide basic understanding of LULCC on the regional climate, and to evaluate the sensitivity of the seasonal variability of the West African Monsoon to LULCC. The prescribed LULCC is based on the changes from 1950 through 1990, representing a maximum feasible degradation scenario in the past half century. It is applied to 5 state of the art global climate models (GCMs) over a 6-year simulation period. Multiple GCMs are used because the magnitude of the impact of LULCC depends on model-dependent coupling strength between the surface and the overlying atmosphere, the magnitude of the surface biophysical changes, and how the key processes linking the surface with the atmosphere are parameterized within a particular model framework. Land cover maps and surface parameters may vary widely among models; therefore a special effort was made to impose consistent biogeophysical responses of surface parameters to LULCC using a simple experimental setup. The prescribed LULCC corresponds to degraded vegetation conditions, which mainly cause increases in the Bowen ratio and decreases in the surface net radiation, and result in a significant reduction in surface evaporation (upwards of 1 mm day over a large part of the Sahel). This, in turn, mainly leads to less moisture convergence and precipitation over the LULCC zone. The overall impact is a rainfall reduction with every model, which ranges across models from 4 to 25 % averaged over the Sahel, and a southward shift of the rainfall peak in three of the five models which evokes a precipitation dipole pattern which is consistent with the observed pattern for dry climate anomalies over this region. The African Easterly Jet shifts equator-ward, although the strength of this change varies considerably among the models. In most of the models, the main factor causing diabatic cooling of the upper troposphere and enhanced subsidence over the region of LULCC is the reduction of convective heating rates linked to reduced latent heat flux and moisture flux convergence. In broad agreement with previous studies, the impact of degradation on the regional climate is found to vary among the different models, however, the signal is stronger and more consistent between the models here than in previous inter-comparison projects. This is likely related to our emphasis on prioritizing a consistent impact of LULCC on the surface biophysical properties. [ABSTRACT FROM AUTHOR]

The actual dynamics and physical mechanisms affecting the Sahel precipitation pattern and amplitude in the climate models remain under debate due to the inconsistent drying and rainfall variability/pattern among them. We diagnose the boreal summer rainfall pattern in the Sahel and its possible causes using short-range ensemble hindcasts based on NCAR community atmospheric model with the local ensemble transform Kalman filter (CAM-LETKF) data assimilation. The CAM-LETKF assimilation was conducted using 64 ensemble members with an assimilation cycle of 6-h. By comparing the superior and inferior groups within these 64 ensembles, we confirmed the influence of the Atlantic in the West Sahel rainfall (a robust feature in the ensembles) and a severe model bias resulting from erroneously modeled locations and magnitudes of low-level Sahara heat low (SHL) and African easterly jet (AEJ). This bias is highly related to atmospheric jet dynamics as shown in recent studies and local wave instability triggered mainly by the boundary-layer temperature gradient and amplified by land-atmosphere interactions. In particular, our results demonstrated that more accurate divergence and convergence fields resulting from improved SHL and AEJ in the superior groups enabled more accurate rainbelt patterns to be discerned, thus improving the ensemble mean model hindcast prediction by more than 25 % in precipitation and 16 % in temperature. We concluded that the use of low-resolution climate models to project future rainfall in the Sahel requires caution because the model hindcasts may quickly diverge even the same boundary conditions and forcings are applied. The model bias may easily grow up within a few months in the short-range CAM-LETKF hindcast, let along the free model centennial simulations. Unconstrained future climate model projections for the Sahel must more effectively capture the short-term key boundary-layer dynamics in the boreal summer to be credible regardless model dynamics and physics. [ABSTRACT FROM AUTHOR]

Regional climate modelling studies often begin by downscaling a reanalysis dataset in order to simulate the observed climate, allowing the investigation of regional climate processes and quantification of the errors associated with the regional model. To date choice of reanalysis to perform such downscaling has been made based either on convenience or on performance of the reanalyses within the regional domain for relevant variables such as near-surface air temperature and precipitation. However, the only information passed from the reanalysis to the regional model are the atmospheric temperature, moisture and winds at the location of the boundaries of the regional domain. Here we present a methodology to evaluate reanalyses derived lateral boundary conditions for an example domain over southern Africa using satellite data. This study focusses on atmospheric temperature and moisture which are easily available. Five commonly used global reanalyses (NCEP1, NCEP2, ERA-I, 20CRv2, and MERRA) are evaluated against the Atmospheric Infrared Sounder satellite temperature and relative humidity over boundaries of two domains centred on southern Africa for the years 2003-2012 inclusive. The study reveals that MERRA is the most suitable for climate mean with NCEP1 the next most suitable. For climate variability, ERA-I is the best followed by MERRA. Overall, MERRA is preferred for generating lateral boundary conditions for this domain, followed by ERA-I. While a 'better' LBC specification is not the sole precursor to an improved downscaling outcome, any reduction in uncertainty associated with the specification of LBCs is a step in the right direction. [ABSTRACT FROM AUTHOR]

In this study, we investigate and quantify different contributors to inter-model differences in regional precipitation projections among CMIP5 climate models. Contributors to the spread are very contrasted between land and ocean. While circulation changes dominate the spread over oceans and continental coasts, thermodynamic changes associated with water vapor increase dominate over inland regions. The inter-model spread in the dynamic component is associated with the change in atmospheric radiative cooling with warming, which largely relates to atmospheric cloud radiative effects. Differences in the thermodynamic component result from the differences in the change in surface evaporation that is explained by decreases in surface humidity and limited surface water availability over land. Secondary contributions to the inter-model spread in thermodynamic and dynamic components result respectively from present-day climatology (owing to the Clausius-Clapeyron scaling) and from the shape of the vertical velocity profile associated with changes in surface temperature gradients. Advancing the physical understanding of the cloud-circulation and precipitation-evaporation couplings and improving their representation in climate models may stand the best chance to reduce uncertainty in regional precipitation projections. [ABSTRACT FROM AUTHOR]

A dynamical downscaling is performed to improve the regional climate simulation in China. It consists of using a variable resolution model LMDZ4 nested into three global climate models (GCMs): BCC-csm1-1-m, FGOALS-g2 and IPSL-CM5A-MR, respectively. The regional climate from different simulations is assessed in terms of surface air temperature and rainfalls through a comparison to observations (both station data and gridded data). The comparison includes climatic trends during the last 40 years, statistical distribution of sub-regional climate, and the seasonal cycle. For surface air temperature, a significant part of the improvement provided by LMDZ4 is related to the effect of surface elevation which is more realistic in high-resolution simulations; the rest is related to changes in regional or local atmospheric general circulation. All GCMs and the downscaling model LMDZ4 are, more or less, able to describe the spatial distribution of surface air temperature and precipitation in China. LMDZ4 does show its superiority, compared to GCMs, in depicting a good regional terrain including the Tibetan Plateau, the Sichuan Basin and the Qilian Mountains. [ABSTRACT FROM AUTHOR]

Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately. [ABSTRACT FROM AUTHOR]

In this study, role of North Tropical Atlantic (NTA) SST on the ENSO variability is examined with CMIP3 and CMIP5 simulations. It is found that most climate models involved in CMIP3 and CMIP5 successfully simulate the inverse relationship between NTA SST during the boreal spring and the ENSO during the subsequent boreal winter. The multi-model ensemble (MME) results show the observed westward propagating signals related to NTA SST from the Atlantic to the Pacific along the off-equatorial Pacific ITCZ. However, different from the observational argument, the main mechanism for the NTA to induce the ENSO is likely to be different in the MME. While the observational result exhibits the NTA-induced off-equatorial Rossby waves play a more dominant role in leading the Pacific signal, the equatorial wind over the western Pacific related to the NTA-induced Kelvin wave is likely to be more crucial to lead the Pacific variability. In addition, the amplitude of NTA SST-induced ENSO in the MME tends to be systematically weaker, and the preference for the central Pacific SST anomaly is also weak. These weak signals are distinctly improved in a model that simulates two types of El Nino events independently. That the strength of the NTA effect to the Pacific can be affected by the seasonal distribution of climatological precipitation is also discussed. Additionally, the strength of the NTA effect tends to be stronger when the model simulates phase locking of ENSO reasonably. [ABSTRACT FROM AUTHOR]

Projections based on climate model ensembles commonly assume that each individual model simulation is of equal value. When combining simulations to estimate the mean and variance of quantities of interest, they are typically unweighted. Exceptions to this approach usually fall into two categories. First, ensembles may be pared down by removing either poorly performing model simulations or model simulations that are perceived to add little additional information, typically where multiple simulations have come from the same model. Second, weighting methodologies, usually based on model performance differences, may be applied, and lead to some improvement in the projected mean. Here we compare the effect of three different weighting techniques-simple averaging, performance based weighting, and weighting that accounts for model dependence-on three ensembles generated by different approaches to model perturbation. We examine the effect of each weighting technique on both the ensemble mean and variance. For comparison, we also consider the effect on the CMIP5 ensemble. While performance weighting is shown to improve the estimate of the mean, it does not appear to improve estimates of ensemble variance, and may in fact degrade them. In contrast, the model independence weighting approach appears to improve both the ensemble mean and the variance in all ensembles. [ABSTRACT FROM AUTHOR]

Large-scale meteorological patterns (LSMPs) associated with temperature extremes are evaluated in a suite of regional climate model (RCM) simulations contributing to the North American Regional Climate Change Assessment Program. LSMPs are characterized through composites of surface air temperature, sea level pressure, and 500 hPa geopotential height anomalies concurrent with extreme temperature days. Six of the seventeen RCM simulations are driven by boundary conditions from reanalysis while the other eleven are driven by one of four global climate models (GCMs). Four illustrative case studies are analyzed in detail. Model fidelity in LSMP spatial representation is high for cold winter extremes near Chicago. Winter warm extremes are captured by most RCMs in northern California, with some notable exceptions. Model fidelity is lower for cool summer days near Houston and extreme summer heat events in the Ohio Valley. Physical interpretation of these patterns and identification of well-simulated cases, such as for Chicago, boosts confidence in the ability of these models to simulate days in the tails of the temperature distribution. Results appear consistent with the expectation that the ability of an RCM to reproduce a realistically shaped frequency distribution for temperature, especially at the tails, is related to its fidelity in simulating LMSPs. Each ensemble member is ranked for its ability to reproduce LSMPs associated with observed warm and cold extremes, identifying systematically high performing RCMs and the GCMs that provide superior boundary forcing. The methodology developed here provides a framework for identifying regions where further process-based evaluation would improve the understanding of simulation error and help guide future model improvement and downscaling efforts. [ABSTRACT FROM AUTHOR]

The effects of large-scale wind forcing on the bimodality of the Kuroshio path south of Japan, the large meander (LM) and non-large meander (NLM), were studied by using a historical simulation (1948-2007) with a high-resolution Ocean general circulation models (OGCM). The Kuroshio in this simulation spent much time in the NLM state, and reproduced several aspects of its long-term path variability for the first time in historical OGCM simulation, presumably because the eddy kinetic energy was kept at a moderate level. By using the simulated fields, the relationships between wind forcing (or Kuroshio transport) and path variation proposed by past studies were tested, and specific roles of eddies in those variations were investigated. The long-term variation of the simulated net Kuroshio transport south of Japan was largely explained by the linear baroclinic Rossby wave adjustment to wind forcing. In the simulated LM events, a triggering meander originated from the interaction of a wind-induced positive sea surface height (SSH) anomaly with the upstream Kuroshio and was enlarged by cyclonic eddies from the recirculation gyre. The cyclonic eddy of the trigger meander was followed by a sizable anticyclonic eddy on the upstream side. Subsequently, a weak (strong) Kuroshio favored the LM (NLM). The LM tended to be maintained when the Kuroshio transport off southern Japan was small, and increasing Kuroshio transport promoted decay of an existing LM. The supply of disturbances from upstream, which is related to the wind-induced SSH variability at low latitudes, contributed to the maintenance of an existing LM. [ABSTRACT FROM AUTHOR]

This study examines the ability of Community Atmosphere Model (CAM) and Community Climate System Model (CCSM) to simulate the Asian summer monsoon, focusing particularly on inter-model comparison and the role of air-sea interaction. Two different versions of CAM, namely CAM4 and CAM5, are used for uncoupled simulations whereas coupled simulations are performed with CCSM4 model. Ensemble uncoupled simulations are performed for a 30 year time period whereas the coupled model is integrated for 100 years. Emphasis is placed on the simulation of monsoon precipitation by analyzing the interannual variability of the atmosphere-only simulations and sea surface temperature bias in the coupled simulation. It is found that both CAM4 and CAM5 adequately simulated monsoon precipitation, and considerably reduced systematic errors that occurred in predecessors of CAM4, although both tend to overestimate monsoon precipitation when compared with observations. The onset and cessation of the precipitation annual cycle, along with the mean climatology, are reasonably well captured in their simulations. In terms of monsoon interannual variability and its teleconnection with SST over the Pacific and Indian Ocean, both CAM4 and CAM5 showed modest skill. CAM5, with revised model physics, has significantly improved the simulation of the monsoon mean climatology and showed better skill than CAM4. Using idealized experiments with CAM5, it is seen that the adoption of new boundary layer schemes in CAM5 contributes the most to reduce the monsoon overestimation bias in its simulation. In the CCSM4 coupled simulations, several aspects of the monsoon simulation are improved by the inclusion of air-sea interaction, including the cross-variability of simulated precipitation and SST. A significant improvement is seen in the spatial distribution of monsoon mean climatology where a too-heavy monsoon precipitation, which occurred in CAM4, is rectified. A detailed investigation of this significant precipitation reduction showed that the large systematic cold SST errors in the Northern Indian Ocean reduces monsoon precipitation and delays onset by weakening local evaporation. Sensitivity experiments with CAM4 further confirmed these results by simulating a weak monsoon in the presence of cold biases in the Northern Indian Ocean. It is found that although the air-sea coupling rectifies the major weaknesses of the monsoon simulation, the SST bias in coupled simulations induces significant differences in monsoon precipitation. The overall simulation characteristics demonstrate that although the new model versions CAM4, CAM5 and CCSM4, are significantly improved, they still have major weaknesses in simulating Asian monsoon precipitation. [ABSTRACT FROM AUTHOR]

This study discusses and compares three different strategies used to deal with model error in seasonal and decadal forecasts. The strategies discussed are the so-called full initialisation, anomaly initialisation and flux correction. In the full initialisation the coupled model is initialised to a state close to the real-world attractor and after initialisation the model drifts towards its own attractor, giving rise to model bias. The anomaly initialisation aims to initialise the model close to its own attractor, by initialising only the anomalies. The flux correction strategy aims to keep the model trajectory close to the real-world attractor by adding empirical corrections. These three strategies have been implemented in the ECMWF coupled model, and are evaluated at seasonal and decadal time-scales. The practical implications of the different strategies are also discussed. Results show that full initialisation results in a clear model drift towards a colder climate. The anomaly initialisation is able to reduce the drift, by initialising around the model mean state. However, the erroneous model mean state results in degraded seasonal forecast skill. The best results on the seasonal time-scale are obtained using momentum-flux correction, mainly because it avoids the positive feedback responsible for a strong cold bias in the tropical Pacific. It is likely that these results are model dependent: the coupled model used here shows a strong cold bias in the Central Pacific, resulting from a positive coupled feedback between winds and SST. At decadal time-scales it is difficult to determine whether any of the strategies is superior to the others. [ABSTRACT FROM AUTHOR]

The future changes of atmospheric blocking over the Euro-Atlantic sector, diagnosed from an ensemble of 17 global-climate simulations obtained with the ECHAM5/MPI-OM model, are shown to be largely explainable from the change of the 500 hPa mean zonal circulation and its variance. The reduction of the blocking frequency over the Atlantic and the increased frequency of easterly upper-level flow poleward of 60°N are well explained by the changes of mean zonal circulation. In winter and autumn an additional downstream shift of the frequency maximum is simulated. This is also seen in a subset of the CMIP5 models with RCP8.5. To explain this downstream shift requires the inclusion of the changing variance. It is suggested that the increased downstream variance is caused by the stronger, more eastward extending future jet, which promotes Rossby wave breaking and blocking to occur further downstream. The same relation between jet-strength and central-blocking longitude is found in the variability of the current climate. [ABSTRACT FROM AUTHOR]

Large parts of western and central Europe face a 20-50 % future reduction in snowfall on Hellmann days (days with daily-mean temperatures below freezing). This strong reduction occurs in addition to the expected 75 % decrease of the number of Hellmann days near the end of the twenty first century. The result is insensitive to the exact freezing-level threshold, but is in sharp contrast with the winter daily precipitation, which increases under most global warming scenarios. Not only climate model simulations show this. Observational records also reveal that probabilities for precipitation on Hellmann days have been larger in the past. The future reduction is a consequence of the freezing-level threshold becoming a more extreme quantile of the temperature distribution in the future. Only certain circulation types permit these quantiles to be reached, and it is shown that these have intrinsically low precipitation probability. [ABSTRACT FROM AUTHOR]

State-of-the-art coupled global climate models are evaluated for their simulation of the Atlantic Warm Pool (AWP). Historical runs from 17 coupled climate models included in the Fifth Phase of the Coupled Model Intercomparison Project (CMIP5) serve as the basis for this model evaluation study. The model simulations are directly compared to observations and reanalysis data to evaluate the climatological features and variability of the AWP within each individual model. Results reveal that a select number of models-namely the GISS-E2-R, CSIRO-Mk3.6, and MPI-ESM-LR-are successful at resolving an appropriately sized AWP with some reasonable climatological features. However, these three models exhibit an erroneously broad seasonal peak of the AWP, and its variability is significantly underestimated. Furthermore, all of the CMIP5 models exhibit a significant cold bias across the tropical Atlantic basin, which hinders their ability to accurately resolve the AWP. [ABSTRACT FROM AUTHOR]

The objective of this work is to gain a general insight into the key mechanisms involved in the impact of nudging on the large scales and the small scales of a regional climate simulation. A 'Big Brother experiment' (BBE) approach is used where a 'reference atmosphere' is known, unlike when regional climate models are used in practice. The main focus is on the sensitivity to nudging time, but the BBE approach allows to go beyond a pure sensitivity study by providing a reference which model outputs try to approach, defining an optimal nudging time. Elaborating upon previous idealized studies, this work introduces key novel points. The BBE approach to optimal nudging is used with a realistic model, here the weather research and forecasting model over the European and Mediterranean regions. A winter simulation (1 December 1989-28 February 1990) and a summer simulation (1 June 1999-31 August 1999) with a 50 km horizontal mesh grid have been performed with initial and boundary conditions provided by the ERA-interim reanalysis of the European Center for Medium-range Weather Forecast to produce the 'reference atmosphere'. The impacts of spectral and indiscriminate nudging are compared all others things being equal and as a function of nudging time. The impact of other numerical parameters, specifically the domain size and update frequency of the large-scale driving fields, on the sensitivity of the optimal nudging time is investigated. The nudged simulations are also compared to non-nudged simulations. Similarity between the reference and the simulations is evaluated for the surface temperature, surface wind and for rainfall, key variables for climate variability analysis and impact studies. These variables are located in the planetary boundary layer, which is not subject to nudging. Regarding the determination of a possible optimal nudging time, the conclusion is not the same for indiscriminate nudging (IN) and spectral nudging and depends on the update frequency of the driving large-scale fields τ. For IN, the optimal nudging time is around τ = 3 h for almost all cases. For spectral nudging, the best results are for the smallest value of τ used for the simulations (τ = 1 h) for frequent update of the driving large-scale fields (3 and 6 h). The optimal nudging time is 3 for 12 h interval between two consecutive driving large-scale fields due to time sampling errors. In terms of resemblance to the reference fields, the differences between the simulations performed with IN and spectral nudging are small. A possible reason for this very similar performance is that nudging is active only above the planetary boundary layer where small-scale features are less energetic. As expected from previous studies, the impact of nudging is weaker for a smaller domain size. However the optimal nudging time itself is not sensitive to domain size. The proposed strategy ensures a dynamical consistency between the driving field and the simulated small-scale field but it does not ensure the best 'observed' fine scale field because of the possible impact of incorrect driving large-scale field. This type of downscaling provides an upper bound on the skill possible for recent historical past and twenty-first century projections. The optimal nudging strategy with respect to dynamic downscaling could add skill whenever the parent global model has some level of skill. [ABSTRACT FROM AUTHOR]

The ability of a large ensemble of regional climate models to accurately simulate heat waves at the regional scale of Europe was evaluated. Within the EURO-CORDEX project, several state-of-the art models, including non-hydrostatic meso-scale models, were run for an extended time period (20 years) at high resolution (12 km), over a large domain allowing for the first time the simultaneous representation of atmospheric phenomena over a large range of spatial scales. Eight models were run in this configuration, and thirteen models were run at a classical resolution of 50 km. The models were driven with the same boundary conditions, the ERA-Interim re-analysis, and except for one simulation, no observations were assimilated in the inner domain. Results, which are compared with daily temperature and precipitation observations (ECA&D and E-OBS data sets) show that, even forced by the same re-analysis, the ensemble exhibits a large spread. A preliminary analysis of the sources of spread, using in particular simulations of the same model with different parameterizations, shows that the simulation of hot temperature is primarily sensitive to the convection and the microphysics schemes, which affect incoming energy and the Bowen ratio. Further, most models exhibit an overestimation of summertime temperature extremes in Mediterranean regions and an underestimation over Scandinavia. Even after bias removal, the simulated heat wave events were found to be too persistent, but a higher resolution reduced this deficiency. The amplitude of events as well as the variability beyond the 90th percentile threshold were found to be too strong in almost all simulations and increasing resolution did not generally improve this deficiency. Resolution increase was also shown to induce large-scale 90th percentile warming or cooling for some models, with beneficial or detrimental effects on the overall biases. Even though full causality cannot be established on the basis of this evaluation work, the drivers of such regional differences were shown to be linked to changes in precipitation due to resolution changes, affecting the energy partitioning. Finally, the inter-annual sequence of hot summers over central/southern Europe was found to be fairly well simulated in most experiments despite an overestimation of the number of hot days and of the variability. The accurate simulation of inter-annual variability for a few models is independent of the model bias. This indicates that internal variability of high summer temperatures should not play a major role in controlling inter-annual variability. Despite some improvements, especially along coastlines, the analyses conducted here did not allow us to generally conclude that a higher resolution is clearly beneficial for a correct representation of heat waves by regional climate models. Even though local-scale feedbacks should be better represented at high resolution, combinations of parameterizations have to be improved or adapted accordingly. [ABSTRACT FROM AUTHOR]

The boreal summer Asian monsoon has been evaluated in 25 Coupled Model Intercomparison Project-5 (CMIP5) and 22 CMIP3 GCM simulations of the late twentieth Century. Diagnostics and skill metrics have been calculated to assess the time-mean, climatological annual cycle, interannual variability, and intraseasonal variability. Progress has been made in modeling these aspects of the monsoon, though there is no single model that best represents all of these aspects of the monsoon. The CMIP5 multi-model mean (MMM) is more skillful than the CMIP3 MMM for all diagnostics in terms of the skill of simulating pattern correlations with respect to observations. Additionally, for rainfall/convection the MMM outperforms the individual models for the time mean, the interannual variability of the East Asian monsoon, and intraseasonal variability. The pattern correlation of the time (pentad) of monsoon peak and withdrawal is better simulated than that of monsoon onset. The onset of the monsoon over India is typically too late in the models. The extension of the monsoon over eastern China, Korea, and Japan is underestimated, while it is overestimated over the subtropical western/central Pacific Ocean. The anti-correlation between anomalies of all-India rainfall and Niño3.4 sea surface temperature is overly strong in CMIP3 and typically too weak in CMIP5. For both the ENSO-monsoon teleconnection and the East Asian zonal wind-rainfall teleconnection, the MMM interannual rainfall anomalies are weak compared to observations. Though simulation of intraseasonal variability remains problematic, several models show improved skill at representing the northward propagation of convection and the development of the tilted band of convection that extends from India to the equatorial west Pacific. The MMM also well represents the space-time evolution of intraseasonal outgoing longwave radiation anomalies. Caution is necessary when using GPCP and CMAP rainfall to validate (1) the time-mean rainfall, as there are systematic differences over ocean and land between these two data sets, and (2) the timing of monsoon withdrawal over India, where the smooth southward progression seen in India Meteorological Department data is better realized in CMAP data compared to GPCP data. [ABSTRACT FROM AUTHOR]

Lagged ensembles from the operational Climate Forecast System version 2 (CFSv2) seasonal hindcast dataset are used to assess skill in forecasting interannual variability of the December-February Arctic Oscillation (AO). We find that a small but statistically significant portion of the interannual variance (>20 %) of the wintertime AO can be predicted at leads up to 2 months using lagged ensemble averages. As far as we are aware, this is the first study to demonstrate that an operational model has discernible skill in predicting AO variability on seasonal timescales. We find that the CFS forecast skill is slightly higher when a weighted ensemble is used that rewards forecast runs with the most accurate representations of October Eurasian snow cover extent (SCE), hinting that a stratospheric pathway linking October Eurasian SCE with the AO may be responsible for the model skill. However, further analysis reveals that the CFS is unable to capture many important aspects of this stratospheric mechanism. Model deficiencies identified include: (1) the CFS significantly underestimates the observed variance in October Eurasian SCE, (2) the CFS fails to translate surface pressure anomalies associated with SCE anomalies into vertically propagating waves, and (3) stratospheric AO patterns in the CFS fail to propagate downward through the tropopause to the surface. Thus, alternate boundary forcings are likely contributing to model skill. Improving model deficiencies identified in this study may lead to even more skillful predictions of wintertime AO variability in future versions of the CFS. [ABSTRACT FROM AUTHOR]

This work assesses the influence of the model physics in present-day regional climate simulations. It is based on a multi-phyiscs ensemble of 30-year long MM5 hindcasted simulations performed over a complex and climatically heterogeneous domain as the Iberian Peninsula. The ensemble consists of eight members that results from combining different parametrization schemes for modeling the Planetary Boundary Layer, the cumulus and the microphysics processes. The analysis is made at the seasonal time scale and focuses on mean values and interannual variability of temperature and precipitation. The objectives are (1) to evaluate and characterize differences among the simulations attributable to changes in the physical options of the regional model, and (2) to identify the most suitable parametrization schemes and understand the underlying mechanisms causing that some schemes perform better than others. The results confirm the paramount importance of the model physics, showing that the spread among the various simulations is of comparable magnitude to the spread obtained in similar multi-model ensembles. This suggests that most of the spread obtained in multi-model ensembles could be attributable to the different physical configurations employed in the various models. Second, we obtain that no single ensemble member outperforms the others in every situation. Nevertheless, some particular schemes display a better performance. On the one hand, the non-local MRF PBL scheme reduces the cold bias of the simulations throughout the year compared to the local Eta model. The reason is that the former simulates deeper mixing layers. On the other hand, the Grell parametrization scheme for cumulus produces smaller amount of precipitation in the summer season compared to the more complex Kain-Fritsch scheme by reducing the overestimation in the simulated frequency of the convective precipitation events. Consequently, the interannual variability of precipitation (temperature) diminishes (increases), which implies a better agreement with the observations in both cases. Although these features improve in general the accuracy of the simulations, controversial nuances are also highlighted. [ABSTRACT FROM AUTHOR]

In order to model stratocumulus clouds and coastal fog, we have coupled the University of Washington boundary layer model to the regional climate model, RegCM (RegCM-UW). By comparing fog occurrences observed at various coastal airports in the western United States, we show that RegCM-UW has success at modeling the spatial and temporal (diurnal, seasonal, and interannual) climatology of northern California coastal fog. The quality of the modeled fog estimate depends on whether coast-adjacent ocean or land grid cells are used; for the model runs shown here, the oceanic grid cells seem to be most appropriate. The interannual variability of oceanic northern California summertime fog, from a multi-decadal simulation, has a high and statistically significant correlation with the observed interannual variability ( r = 0.72), which indicates that RegCM-UW is capable of investigating the response of fog to long-term climatological forcing. While RegCM-UW has a number of aspects that would benefit from further investigation and development, RegCM-UW is a new tool for investigating the climatology of coastal fog and the physical processes that govern it. We expect that with appropriate physical parameterizations and moderate horizontal resolution, other climate models should be capable of simulating coastal fog. The source code for RegCM-UW is publicly available, under the GNU license, through the International Centre for Theoretical Physics. [ABSTRACT FROM AUTHOR]

Recently, Räisänen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. [ABSTRACT FROM AUTHOR]

Sea-level change is often considered to be globally uniform in sea-level projections. However, local relative sea-level (RSL) change can deviate substantially from the global mean. Here, we present maps of twenty-first century local RSL change estimates based on an ensemble of coupled climate model simulations for three emission scenarios. In the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4), the same model simulations were used for their projections of global mean sea-level rise. The contribution of the small glaciers and ice caps to local RSL change is calculated with a glacier model, based on a volume-area approach. The contributions of the Greenland and Antarctic ice sheets are obtained from IPCC AR4 estimates. The RSL distribution resulting from the land ice mass changes is then calculated by solving the sea-level equation for a rotating, elastic Earth model. Next, we add the pattern of steric RSL changes obtained from the coupled climate models and a model estimate for the effect of Glacial Isostatic Adjustment. The resulting ensemble mean RSL pattern reveals that many regions will experience RSL changes that differ substantially from the global mean. For the A1B ensemble, local RSL change values range from −3.91 to 0.79 m, with a global mean of 0.47 m. Although the RSL amplitude differs, the spatial patterns are similar for all three emission scenarios. The spread in the projections is dominated by the distribution of the steric contribution, at least for the processes included in this study. Extreme ice loss scenarios may alter this picture. For individual sites, we find a standard deviation for the combined contributions of approximately 10 cm, regardless of emission scenario. [ABSTRACT FROM AUTHOR]

The Atlantic meridional overturning circulation (AMOC) in the last 250 years of the 700-year-long present-day control integration of the Community Climate System Model version 3 with T85 atmospheric resolution exhibits a red noise-like irregular multi-decadal variability with a persistence longer than 10 years, which markedly contrasts with the preceding ~300 years of very regular and stronger AMOC variability with ~20 year periodicity. The red noise-like multi-decadal AMOC variability is primarily forced by the surface fluxes associated with stochastic changes in the North Atlantic Oscillation (NAO) that intensify and shift northward the deep convection in the Labrador Sea. However, the persistence of the AMOC and the associated oceanic anomalies that are directly forced by the NAO forcing does not exceed about 5 years. The additional persistence originates from anomalous horizontal advection and vertical mixing, which generate density anomalies on the continental shelf along the eastern boundary of the subpolar gyre. These anomalies are subsequently advected by the mean boundary current into the northern part of the Labrador Sea convection region, reinforcing the density changes directly forced by the NAO. As no evidence was found of a clear two-way coupling with the atmosphere, the multi-decadal AMOC variability in the last 250 years of the integration is an ocean-only response to stochastic NAO forcing with a delayed positive feedback caused by the changes in the horizontal ocean circulation. [ABSTRACT FROM AUTHOR]

The possibility of applying either the maximum entropy production conjecture of Paltridge (Q J R Meteorol Soc 101:475-484, ) or the conjecture of Lorenz (Generation of available potential energy and the intensity of the general circulation. Pergamon, Tarrytown, ) of maximum generation of available potential energy (APE) in FAMOUS, a complex but low-resolution AOGCM, is explored by varying some model parameters to which the simulated climate is highly sensitive, particularly the convective entrainment rate, $$\epsilon$$, and cloud droplet-to-rain-conversion rate, c. The climate response is analysed in terms of its entropy production and the strength of the Lorenz energy cycle. If either conjecture is true, the parameter values which yield the most realistic climate will also maximise the relevant quantity. No maximum is found in the total material entropy production, which is dominated by the hydrological cycle and tends to increase monotonically with global-mean temperature, which is not constant because the parameter variations affect the net input of solar radiation at the top of the atmosphere (TOA). In contrast, there is a non-monotonic, peaked behaviour in the generation of APE and entropy production associated with kinetic energy dissipation, with the standard FAMOUS values for $$\epsilon$$ and c occurring nearly at the maximising ones. The maximum states are shown to be states of vigorous baroclinic activity. The peak in the generation of APE appears to be related to a trade-off between the mean vertical stability and horizontal stratification. Experiments are repeated for a simplified setup in which the net solar input at TOA is fixed. Again a peak in the generation of APE is found in association with the maximum baroclinic activity, but no trade-off of the kind shown by simple climate models is found between meridional heat transport and the meridional temperature gradient. We conclude that the maximum entropy production conjecture does not hold within the climate system when the effects of the hydrological cycle and radiative feedbacks are taken into account, but our experiments provide some evidence in support of the conjecture of maximum APE production (or equivalently maximum dissipation of kinetic energy). [ABSTRACT FROM AUTHOR]

The spatial resolution gap between global or regional climate models and the requirements for local impact studies motivates the need for climate downscaling. For impact studies that involve glacier modelling, the sparsity or complete absence of climate monitoring activities within the regions of interest presents a substantial additional challenge. Downscaling methods for this application must be independent of climate observations and cannot rely on tuning to station data. We present new, computationally-efficient methods for downscaling precipitation and temperature to the high spatial resolutions required to force mountain glacier models. Our precipitation downscaling is based on an existing linear theory for orographic precipitation, which we modify for large study regions by including moist air tracking. Temperature is downscaled using an interpolation scheme that reconstructs the vertical temperature structure to estimate surface temperatures from upper air data. Both methods are able to produce output on km to sub-km spatial resolution, yet do not require tuning to station measurements. By comparing our downscaled precipitation (1 km resolution) and temperature (200 m resolution) fields to station measurements in southern British Columbia, we evaluate their performance regionally and through the annual cycle. Precipitation is improved by as much as 30% (median relative error) over the input reanalysis data and temperature is reconstructed with a mean bias of 0.5°C at locations with high vertical relief. Both methods perform best in mountainous terrain, where glaciers tend to be concentrated. [ABSTRACT FROM AUTHOR]

Dynamical downscaling of ECHAM5 using HIRHAM5 and RCA3 for a northern European domain focused on Scandinavia indicates sustained extreme wind speeds with long recurrence intervals (50 years) and intense winds are not likely to evolve out of the historical envelope of variability until the end of C21st. Even then, significant changes are indicated only in the SW of the domain and across the central Baltic Sea where there is some evidence for relatively small magnitude increases in the 50 year return period wind speed (of up to 15%). There are marked differences in results based on the two Regional Climate Models. Additionally, internal (inherent) variability and initial conditions exert a strong impact on projected wind climates throughout the twenty-first century. Simulations of wind gusts by one of the RCMs (RCA3) indicate some evidence for increased magnitudes (of up to +10%) in the southwest of the domain and across the central Baltic Sea by the end of the current century. As in prior downscaling of ECHAM4, dynamical downscaling of ECHAM5 indicates a tendency towards increased energy density and thus wind power generation potential over the course of the C21st. However, caution should be used in interpreting this inference given the high degree of wind climate projection spread that derives from the specific AOGCM and RCM used in the downscaling. [ABSTRACT FROM AUTHOR]

A convection scheme for climate model is developed based on Tiedtke's (Mon Weather Rev 117:1779-1800, ) bulk mass flux framework and is evaluated with observational data and cloud resolving model simulation data. The main differences between the present parameterization and Tiedtke's parameterization are the convection trigger, fractional entrainment and detrainment rate formulations, and closure method. Convection is triggered if the vertical velocity of a rising parcel is positive at the level at which the parcel is saturated. The fractional entrainment rate depends on the vertical velocity and buoyancy of the parcel as well as the environmental relative humidity. For the fractional detrainment rate, a linear decrease in the updraft mass flux above maximum buoyancy level is assumed. In the closure method, the cloud base mass flux is determined by considering both cloud layer instability and subcloud layer turbulent kinetic energy as controlling factors in the strength of the convection. The convection scheme is examined in a single column framework as well as using a general circulation model. The present bulk mass flux (BMF) scheme is compared with a simplified Relaxed Arakawa-Schubert (RAS) scheme. In contrast to the RAS, which specifies the cloud top, cloud top height in BMF depends on environmental properties, by considering the conditions of both the parcel and its environment in a fractional entrainment and detrainment rate formulations. As a result, BMF shows improved sensitivity in depth and strength of convection on environmental humidity compared to RAS, by strengthening coupling between cloud and environment. When the mid to lower troposphere is dry, the cloud resolving model and BMF produce cloud top around the dry layer and moisten the layer. In the framework of general circulation model, enhanced coupling between convection and environmental humidity in BMF results in improved representation of eastward propagating intraseasonal variability in the tropics-the Madden-Julian oscillation. [ABSTRACT FROM AUTHOR]

In this article, we study the climate link between the Southern Annular Mode (SAM) and the southern sea-ice extent (SIE), and discuss the possible role of stationary waves and synoptic eddies in establishing this link. In doing so, we have used a combination of techniques involving spatial correlations of SIE, eddy streamfunction and wind anomalies, and statistics of high-latitude cyclone strength. It is suggested that stationary waves may be amplified by eddy anomalies associated with high latitude cyclones, resulting in more sea ice when the SAM is in its positive phase for most, but not all, longitudes. A similar association is observed during ENSO (La Niña years). Although this synergy in the SAM/ENSO response may partially reflect preferential areas for wave amplification around Antarctica, the short extent of the climate records does not allow for a definite causality connection to be established with SIE. Stronger polar cyclones are observed over the areas where the stationary waves are amplified. These deeper cyclones will break up and export ice equatorward more efficiently, but the near-coastal regions are cold enough to allow for a rapid re-freeze of the resulting ice break-up. We speculate that if global warming continues this same effect could help reverse the current (positive) Antarctic SIE trends once the ice gets thinner, similarly to what has been observed in the Northern Hemisphere. [ABSTRACT FROM AUTHOR]

In this study the capability of the MM5 model in simulating the main mode of intraseasonal variability during the warm season over South America is evaluated through a series of sensitivity experiments. Several 3-month simulations nested into ERA40 reanalysis were carried out using different cumulus schemes and planetary boundary layer schemes in an attempt to define the optimal combination of physical parameterizations for simulating alternating wet and dry conditions over La Plata Basin (LPB) and the South Atlantic Convergence Zone regions, respectively. The results were compared with different observational datasets and model evaluation was performed taking into account the spatial distribution of monthly precipitation and daily statistics of precipitation over the target regions. Though every experiment was able to capture the contrasting behavior of the precipitation during the simulated period, precipitation was largely underestimated particularly over the LPB region, mainly due to a misrepresentation in the moisture flux convergence. Experiments using grid nudging of the winds above the planetary boundary layer showed a better performance compared with those in which no constrains were imposed to the regional circulation within the model domain. Overall, no single experiment was found to perform the best over the entire domain and during the two contrasting months. The experiment that outperforms depends on the area of interest, being the simulation using the Grell (Kain-Fritsch) cumulus scheme in combination with the MRF planetary boundary layer scheme more adequate for subtropical (tropical) latitudes. The ensemble of the sensitivity experiments showed a better performance compared with any individual experiment. [ABSTRACT FROM AUTHOR]

Air-sea heat and freshwater water fluxes in the Mediterranean Sea play a crucial role in dense water formation. Here, we compare estimates of Mediterranean Sea heat and water budgets from a range of observational datasets and discuss the main differences between them. Taking into account the closure hypothesis at the Gibraltar Strait, we have built several observational estimates of water and heat budgets by combination of their different observational components. We provide then three estimates for water budget and one for heat budget that satisfy the closure hypothesis. We then use these observational estimates to assess the ability of an ensemble of ERA40-driven high resolution (25 km) Regional Climate Models (RCMs) from the FP6-EU ENSEMBLES database, to simulate the various components, and net values, of the water and heat budgets. Most of the RCM Mediterranean basin means are within the range spanned by the observational estimates of the different budget components, though in some cases the RCMs have a tendency to overestimate the latent heat flux (or evaporation) with respect to observations. The RCMs do not show significant improvements of the total water budget estimates comparing to ERA40. Moreover, given the large spread found in observational estimates of precipitation over the sea, it is difficult to draw conclusions on the performance of RCM for the freshwater budget and this underlines the need for better precipitation observations. The original ERA40 value for the basin mean net heat flux is −15 W/m which is 10 W/m less than the value of −5 W/m inferred from the transport measurements at Gibraltar Strait. The ensemble of heat budget values estimated from the models show that most of RCMs do not achieve heat budget closure. However, the ensemble mean value for the net heat flux is −7 ± 21 W/m, which is close to the Gibraltar value, although the spread between the RCMs is large. Since the RCMs are forced by the same boundary conditions (ERA40 and sea surface temperatures) and have the same horizontal resolution and spatial domain, the reason for the large spread must reside in the physical parameterizations. To conclude, improvements are urgently required to physical parameterizations in state-of-the-art regional climate models, to reduce the large spread found in our analysis and to obtain better water and heat budget estimates over the Mediterranean Sea. [ABSTRACT FROM AUTHOR]

We present results from multiple comprehensive models used to simulate an aggressive mitigation scenario based on detailed results of an Integrated Assessment Model. The experiment employs ten global climate and Earth System models (GCMs and ESMs) and pioneers elements of the long-term experimental design for the forthcoming 5th Intergovernmental Panel on Climate Change assessment. Atmospheric carbon-dioxide concentrations pathways rather than carbon emissions are specified in all models, including five ESMs that contain interactive carbon cycles. Specified forcings also include minor greenhouse gas concentration pathways, ozone concentration, aerosols (via concentrations or precursor emissions) and land use change (in five models). The new aggressive mitigation scenario (E1), constructed using an integrated assessment model (IMAGE 2.4) with reduced fossil fuel use for energy production aimed at stabilizing global warming below 2 K, is studied alongside the medium-high non-mitigation scenario SRES A1B. Resulting twenty-first century global mean warming and precipitation changes for A1B are broadly consistent with previous studies. In E1 twenty-first century global warming remains below 2 K in most models, but global mean precipitation changes are higher than in A1B up to 2065 and consistently higher per degree of warming. The spread in global temperature and precipitation responses is partly attributable to inter-model variations in aerosol loading and representations of aerosol-related radiative forcing effects. Our study illustrates that the benefits of mitigation will not be realised in temperature terms until several decades after emissions reductions begin, and may vary considerably between regions. A subset of the models containing integrated carbon cycles agree that land and ocean sinks remove roughly half of present day anthropogenic carbon emissions from the atmosphere, and that anthropogenic carbon emissions must decrease by at least 50% by 2050 relative to 1990, with further large reductions needed beyond that to achieve the E1 concentrations pathway. Negative allowable anthropogenic carbon emissions at and beyond 2100 cannot be ruled out for the E1 scenario. There is self-consistency between the multi-model ensemble of allowable anthropogenic carbon emissions and the E1 scenario emissions from IMAGE 2.4. [ABSTRACT FROM AUTHOR]