Hydrological changes in the climate system from leaf responses to increasing CO2

Vegetation is a major component of the climate system because of its controls on the energy and water balance over land. This functioning changes because of the physiological response of leaves to increased CO₂. A climate model is used to compare these changes with the climate changes from radiative forcing by greenhouse gases. For this purpose, we use the Community Earth System Model coupled to a slab ocean. Ensemble integrations are done for current and doubled CO₂. The consequent reduction of transpiration and net increase of surface radiative heating from reduction in cloudiness increases the temperature over land by a significant fraction of that directly from the radiative warming by CO₂. Large-scale atmospheric circulation adjustments result. In particular, over the tropics, a low-level westerly wind anomaly develops associated with reduced geopotential height over land, enhancing moisture transport and convergence, and precipitation increases over the western Amazon, the Congo basin, South Africa, and Indonesia, while over mid-latitudes, land precipitation decreases from reduced evapotranspiration. On average, land precipitation is enhanced by 0.03 mm day^?1 (about 19 % of the CO₂ radiative forcing induced increase). This increase of land precipitation with decreased ET is an apparent negative feedback, i.e., less ET makes more precipitation. Global precipitation is slightly reduced. Runoff increases associated with both the increased land precipitation and reduced evapotranspiration. Examining the consistency of the variations among ensemble members shows that vegetation feedbacks on precipitation are more robust over the tropics and in mid to high latitudes than over the subtropics where vegetation is sparse and the internal climate variability has a larger influence.     

Climate Change Scenarios for the Hudson Bay Region: An Intermodel Comparison

General circulation models (GCMs) are unanimous in projecting warmer temperatures in an enhanced CO₂ atmosphere, with amplification of this warming in higher latitudes. The Hudson Bay region, which is located in the Arctic and subarctic regions of Canada, should therefore be strongly influenced by global warming. In this study, we compare the response of Hudson Bay to a transient warming scenario provided by six-coupled atmosphere-ocean models. Our analysis focuses on surface temperature, precipitation, sea-ice coverage, and permafrost distribution. The results show that warming is expected to peak in winter over the ocean, because of a northward retreat of the sea-ice cover. Also, a secondary warming peak is observed in summer over land in the Canadian and Australian-coupled GCMs, which is associated with both a reduction in soil moisture conditions and changes in permafrost distribution. In addition, a relationship is identified between the retreat of the sea-ice cover and an enhancement of precipitation over both land and oceanic surfaces. The response of the sea-ice cover and permafrost layer to global warming varies considerably among models and thus large differences are observed in the projected regional increase in temperature and precipitation. In view of the important feedbacks that a retreat of the sea-ice cover and the distribution of permafrost are likely to play in the doubled and tripled CO₂ climates of Hudson Bay, a good representation of these two parameters is necessary to provide realistic climate change scenarios. The use of higher resolution regional climate model is recommended to develop scenarios of climate change for the Hudson Bay region.     

The impact of doubled CO2 on the energetics and hydrologic processes of mid-latitude transient eddies

The Northern Hemisphere winter (DJF) stationary eddy response of a general circulation model (GCM) to a doubling of atmospheric CO₂ is simulated with a linear steady state model as a response to anomalies in diabatic heating (latent, sensible and radiative), mountain and transient eddy effects. For this analysis the doubled CO₂ experiment performed by Wilson and Mitchell (1987) is used. The linear simulations of the control and perturbation climate capture most of the important features of the GCMs stationary eddies. The simulation of the anomalous stationary eddy pattern in the Northern Hemisphere captures only some of the important features of the GCMs anomalies. The climate anomalies in the Southern Hemisphere are poorly simulated. In the Northern Hemisphere the climate anomalies are dominated by the effect of transient eddies and mountains. In low latitudes also the contribution of latent heating is important. The contributions of sensible and radiative heating are small.     

Simulation of the effect of doubled atmospheric CO2 on the climate of northern and central California

A Local Climate Model (LCM) is described that can provide a high-resolution (10 km) simulation of climate resulting from a doubling of atmospheric CO₂ concentrations. A canonicalregression function is used to compute the monthly temperature (mean of daily-maximum-temperature) and precipitation for any point, given a set of predictor variables. Predictor variables represent the influence of terrain, sea-surface temperature (SST), windfields, CO₂ concentration, and solar radiation on climate. The canonical-regression function is calibrated and validated using empirical windfield, SST, and climate data from stations in the western U.S. To illustrate an application of the LCM, the climate of northern and central California is simulated for a doubled CO₂ (600 ppmv) and a control scenario (300 ppmv CO₂). Windfields and SSTs used to compute predictor variables are taken from general circulation model simulations for these two scenarios. LCM solutions indicate that doubling CO₂ will result in a 3 C° increase in January temperature, a 2 C° increase in July temperature, a 16 mm (37%) increase in January precipitation, and a 3 mm (46%) increase in July precipitation.     

North Atlantic Oscillation response to transient greenhouse gas forcing and the impact on European winter climate: a CMIP2 multi-model assessment

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO₂) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO₂, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5–10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970–1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO₂ concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061±0.0036 hPa per %CO₂. Although an increase of 0.61 hPa in NAO for a doubling in CO₂ represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models’ inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.     

Objective comparison of patterns of CO2 induced climate change in coupled GCM experiments

 Four transient GCM experiments simulating the climatic response to gradually increasing CO₂, and two equilibrium doubled CO₂ experiments are compared. The zonally symmetric and asymmetric features of climate are both examined. Surface air temperature, sea level pressure, the 500 mb height and the relative topography between 500 and 1000 mb are analyzed. In the control simulations, the broad aspects of the present climate are in most cases well reproduced, although the stationary eddies tend to be less reliably simulated than the zonal means. However, the agreement between the four transient experiments on the geographical patterns of climate change is less impressive. While some zonally symmetric features, in particular the meridional distribution of surface air warming in the boreal winter, are rather similar in all models, the intermodel cross correlations for the zonally asymmetric changes are low. The agreement is largely restricted to some very general features such as more warming over the continents than over the oceans. The largest discrepancies between the two equilibrium-doubled CO₂ experiments and the transient experiments are found at the high southern latitudes, in particular in the austral winter. To identify the most robust geographical patterns of change in the transient experiments, the standard t test is used to determine if the four-model mean change is significantly above or below the global mean. Received: 18 January 1996 / Accepted: 5 July 1996     

Multi-model changes in El Niño teleconnections over North America in a future warmer climate

Previous studies with single models have suggested that El Niño teleconnections over North America could be different in a future warmer climate due to factors involving changes of El Niño event amplitude and/or changes in the midlatitude base state circulation. Here we analyze a six-member multi-model ensemble, three models with increasing future El Niño amplitude, and three models with decreasing future El Niño amplitude, to determine characteristics and possible changes to El Niño teleconnections during northern winter over the North Pacific and North America in a future warmer climate. Compared to observed El Niño events, all the models qualitatively produce general features of the observed teleconnection pattern over the North Pacific and North America, with an anomalously deepened Aleutian Low, a ridge over western North America, and anomalous low pressure over the southeastern United States. However, associated with systematic errors in the location of sea surface temperature and convective heating anomalies in the central and western equatorial Pacific (the models’ anomaly patterns are shifted to the west), the anomalous low pressure center in the North Pacific is weaker and shifted somewhat south compared to the observations. For future El Niño events, two different stabilization experiments are analyzed, one with CO₂ held constant at year 2100 concentrations in the SRES A1B scenario (roughly doubled present-day CO₂), and another with CO₂ concentrations held constant at 4XCO₂. Consistent with the earlier single model results, the future El Niño teleconnections are changed in the models, with a weakened as well as an eastward- and northward-shifted anomalous low in the North Pacific. This is associated with weakened anomalous warming over northern North America, strengthened cooling over southern North America, and precipitation increases in the Pacific Northwest in future events compared to present-day El Niño event teleconnections. These changes are consistent with the altered base state upper tropospheric circulation with a wave-5 pattern noted in previous studies that is shown here to be consistent across all the models whether there are projected future increases or decreases in El Niño amplitude. The future teleconnection changes are most consistent with this anomalous wave-5 pattern in the models with future increases of El Niño amplitude, but less so for the models with future decreases of El Niño amplitude.     

Agricultural drought in a future climate: results from 15 global climate models participating in the IPCC 4th assessment

This study examines the impact of greenhouse gas warming on soil moisture based on predictions of 15 global climate models by comparing the after-stabilization climate in the SRESA1b experiment with the pre-industrial control climate. The models are consistent in predicting summer dryness and winter wetness in only part of the northern middle and high latitudes. Slightly over half of the models predict year-round wetness in central Eurasia and/or year-round dryness in Siberia and mid-latitude Northeast Asia. One explanation is offered that relates such lack of seasonality to the carryover effect of soil moisture storage from season to season. In the tropics and subtropics, a decrease of soil moisture is the dominant response. The models are especially consistent in predicting drier soil over the southwest North America, Central America, the Mediterranean, Australia, and the South Africa in all seasons, and over much of the Amazon and West Africa in the June–July–August (JJA) season and the Asian monsoon region in the December–January–February (DJF) season. Since the only major areas of future wetness predicted with a high level of model consistency are part of the northern middle and high latitudes during the non-growing season, it is suggested that greenhouse gas warming will cause a worldwide agricultural drought. Over regions where there is considerable consistency among the analyzed models in predicting the sign of soil moisture changes, there is a wide range of magnitudes of the soil moisture response, indicating a high degree of model dependency in terrestrial hydrological sensitivity. A major part of the inter-model differences in the sensitivity of soil moisture response are attributable to differences in land surface parameterization.     

Developing climate change scenarios for Tamil Nadu, India using MAGICC/SCENGEN

This paper describes the projection of climate change scenarios under increased greenhouse gas emissions, using the results of atmospheric-ocean general circulation models in the Coupled Model Intercomparison Project phase 3 dataset. A score is given to every model based on global and regional performance. Four out of 20 general circulation models (GCMs) were selected based on skill in predicting observed annual temperature and precipitation conditions. The ensemble of these four models shows superiority over the individual model scores. These models were subjected to increases in future anthropogenic radiative forcings for constructing climate change scenarios. Future climate scenarios for Tamil Nadu were developed with MAGICC/SCENGEN software. Model results show both temperature and precipitation increases under increased greenhouse gas scenarios. Northeast and northwest parts of Tamil Nadu show a greater increase in temperature and precipitation. Seasonally, the maximum rise in temperature occurred during the MAM season, followed by DJF, JJA, and SON. Decreasing trends of precipitation were observed during DJF and MAM.     

Influence of dynamic vegetation on climate change arising from increasing CO<Subscript>2</Subscript>

A dynamic global vegetation model (DGVM) is coupled to an atmospheric general circulation model (AGCM) to investigate the influence of vegetation dynamics on climate change under conditions of global warming. The model results are largely in agreement with observations and the results of previous studies in terms of the present climate, present potential vegetation, present net primary productivity (NPP), and pre-industrial carbon budgets. The equilibrium state of climate properties are compared among pre-industrial, doubled, and quadrupled atmospheric CO₂ values using DGVM–AGCM and current AGCM with fixed vegetation to evaluate the influence of dynamic vegetation change. We also separated the contributions of temperature, precipitation and CO₂ fertilization on vegetation change. The results reveal an amplification of global warming climate sensitivity by 10% due to the inclusion of dynamic vegetation. The total effects of elevated CO₂ and climate change also lead to an increase in NPP and vegetation coverage globally. The reduction of albedo associated with this greening results in enhanced global warming. Our separation analysis indicates that temperature alters vegetation at high latitudes such as Siberia or Alaska, where there is a switch from tundra to forest. On the other hand, CO₂ fertilization provides the largest contribution to greening in arid/semi-arid region. Precipitation change did not cause any drastic vegetation shift.     

Quantifying global climate feedbacks, responses and forcing under abrupt and gradual CO2 forcing

Experiments with abrupt CO₂ forcing allow the diagnosis of the response of global mean temperature and precipitation in terms of fast temperature independent adjustments and slow, linear temperature-dependent feedbacks. Here we compare responses, feedbacks and forcings in experiments performed as part of version 5 of the coupled model inter-comparison project (CMIP5). The experiments facilitate, for the first time, a comparison of fully coupled atmosphere-ocean general circulation models (GCM’s) under both linearly increasing and abrupt radiative forcing. In the case of a 1 % per year compounded increase in CO₂ concentration, we find that the non-linear evolution of surface air temperature in time, when combined with the linear evolution of the radiative balance at the top of the atmosphere, results in a feedback parameter and effective climate sensitivity having an offset compared to values computed from abrupt 4× CO₂ forcing experiments. The linear evolution of the radiative balance at the top of the atmosphere also contributes to an offset between the global mean precipitation response predicted in the 1 % experiment using linear theory and that diagnosed from the experiments themselves, and a potential error between the adjusted radiative forcing and that produced using a standard linear formula. The non-linear evolution of temperature and precipitation responses are also evident in the RCP8.5 scenario and have implications for understanding, quantifying and emulating the global response of the CMIP5 climate GCMs.     

Deep-ocean heat uptake and equilibrium climate response

We integrate the coupled climate model ECHAM5/MPIOM to equilibrium under atmospheric CO₂ quadrupling. The equilibrium global-mean surface-temperature change is 10.8 K. The surface equilibrates within about 1,200 years, the deep ocean within 5,000 years. The impact of the deep ocean on the equilibrium surface-temperature response is illustrated by the difference between ECHAM5/MPIOM and ECHAM5 coupled with slab ocean model (ECHAM5/SOM). The equilibrium global-mean surface temperature response is 11.1 K in ECHAM5/SOM and is thus 0.3 K higher than in ECHAM5/MPIOM. ECHAM5/MPIOM shows less warming over the northern-hemisphere mid and high latitudes, but larger warming over the tropical ocean and especially over the southern-hemisphere high latitudes. ECHAM5/MPIOM shows similar polar amplification in both the Arctic and the Antarctic, in contrast to ECHAM5/SOM, which shows stronger polar amplification in the northern hemisphere. The southern polar warming in ECHAM5/MPIOM is greatly delayed by Antarctic deep-ocean warming due to convective and isopycnal mixing. The equilibrium ocean temperature warming under CO₂ quadrupling is around 8.0 K and is near-uniform with depth. The global-mean steric sea-level rise is 5.8 m in equilibrium; of this, 2.3 m are due to the deep-ocean warming after the surface temperature has almost equilibrated. This result suggests that the surface temperature change is a poor predictor for steric sea-level change in the long term. The effective climate response method described in Gregory et al. (2004) is evaluated with our simulation, which shows that their method to estimate the equilibrium climate response is accurate to within 10 %.     

Sensitivity of transient eddies to climate change in the CCC general circulation model

Abstract

We use eddy life‐cycle simulations to evaluate the response of atmospheric transient eddies to a global warming caused by CO₂ doubling in the CCC general circulation model. In simulations using Northern Hemisphere winter conditions, transient waves attain larger kinetic energy and encompass a wider range of latitudes in the warmer climate. This behaviour contrasts with a previous investigation that used output from the NCAR and GFDL models. Our analysis indicates two primary factors for the difference between model responses: (1) a smaller change in the mid‐latitude temperature gradient in the CCC model, which allows (2) increased atmospheric water vapour in mid‐latitudes to catalyze a more rapidly evolving life‐cycle.     

Precipitation Change: Model Simulations and Paleoreconstructions

Zonal-scale patterns of precipitation change, as reconstructed for the Mid-Pliocene and the two Pleistocene optima, are compared with those generated in standard 2 × CO₂–1 × CO₂ equilibrium experiments by two high-resolution GCMs of equal sensitivities of global precipitation and temperature to CO₂ doubling. We find that the three warm paleoclimates, despite differences in boundary conditions/forcings, exhibit a similarity in zonal-scale patterns of change for precipitation over land in the Northern Hemisphere (NH); the between-epoch pattern correlation is 0.9 on the average. The two models give marked differences in zonal distribution of precipitation anomalies at mid-latitudes; the between-model pattern correlation for changes of precipitation over NH land is 0.4. The response of precipitation over the NH land area to the NH warming is about 10%/°C in the paleodata compared to 3%/°C in the models. The largest model/paleodata descrepancy refers to the present-day desert belt, where a large precipitation anomaly persists in all epochs. North of 50 N, the absolute values of the zonally-averaged precipitation anomalies simulated by both models fall in the range implied by the three warm paleoclimates, but they are systematically lower than the anomalies of the Mid-Pliocene. If our reconsructions are valid and if climate changes in the Mid-Pliocene were driven solely by CO₂ changes, then our results suggest that models are underestimating the magnitude of the precipitation response, especially in the regions of subtropical deserts; the magnitude of the simulated temperature response at high latitudes is also underestimated. At least part of the reported model/paleodata discordance appears to be due to lack of interactive land surface package in the models examined.     

Modeling responses of the meadow steppe dominated by Leymus chinensis to climate change

Grassland is one of the most widespread vegetation types worldwide and plays a significant role in regional climate and global carbon cycling. Understanding the sensitivity of Chinese grassland ecosystems to climate change and elevated atmospheric CO₂ and the effect of these changes on the grassland ecosystems is a key issue in global carbon cycling. China encompasses vast grassland areas of 354 million ha of 17 major grassland types, according to a national grassland survey. In this study, a process-based terrestrial model the CENTURY model was used to simulate potential changes in net primary productivity (NPP) and soil organic carbon (SOC) of the Leymus chinensis meadow steppe (LCMS) under different scenarios of climatic change and elevated atmospheric CO₂. The LCMS sensitivities, its potential responses to climate change, and the change in capacity of carbon stock and sequestration in the future are evaluated. The results showed that the LCMS NPP and SOC are sensitive to climatic change and elevated CO₂. In the next 100 years, with doubled CO₂ concentration, if temperature increases from 2.7-3.9˚C and precipitation increases by 10% NPP and SOC will increase by 7-21% and 5-6% respectively. However, if temperature increases by 7.5-7.8˚C and precipitation increases by only 10% NPP and SOC would decrease by 24% and 8% respectively. Therefore, changes in the NPP and SOC of the meadow steppe are attributed mainly to the amount of temperature and precipitation change and the atmospheric CO₂ concentration in the future.     

Intercomparsion of regional biases and doubled CO2-sensitivity of coupled atmosphere-ocean general circulation model experiments

 We compared regional biases and transient doubled CO₂ sensitivities of nine coupled atmosphere-ocean general circulation models (GCMs) from six international climate modeling groups. We evaluated biases and responses in winter and summer surface air temperatures and precipitation for seven subcontinental regions, including those in the 1990 Intergovernmental Panel on Climate Change (IPCC) Scientific Assessment. Regional biases were large and exceeded the variance among four climatological datasets, indicating that model biases were not primarily due to uncertainty in observations. Model responses to altered greenhouse forcing were substantial (average temperature change=2.7±0.9 ^°C, range of precipitation change =−35 to +120% of control). While coupled models include more climate system feedbacks than earlier GCMs implemented with mixed-layer ocean models, inclusion of a dynamic ocean alone did not improve simulation of long-term mean climatology nor increase convergence among model responses to altered greenhouse gas forcing. On the other hand, features of some of the coupled models including flux adjustment (which may have simply masked simulation errors), high horizontal resolution, and estimation of screen height temperature contributed to improved simulation of long-term surface climate. The large range of model responses was partly accounted for by inconsistencies in forcing scenarios and transient-simulation averaging periods. Nonetheless, the models generally had greater agreement in their sensitivities than their controls did with observations. This suggests that consistent, large-scale response features from an ensemble of model sensitivity experiments may not depend on details of their representation of present-day climate. Received: 9 September 1996 / Revised: 31 July 1997     

Anomalies in temperature and rainfall during warm Arctic seasons as a guide to the formulation of climate scenarios

Recently much concern has been expressed regarding the impact of an increased atmospheric CO₂ concentration on climate. Unfortunately, present understanding and models of the climate system are not good enough for reliable prediction of such impacts. This paper presents an analysis of recent climate data in order to illustrate the nature of regional temperature and rainfall changes in different seasons and to provide some guidance with regard to points which might be borne in mind when scenarios of future climate (especially those taking into account human impacts) are being formulated.Since it is believed that an increased atmospheric CO₂ concentration will cause a warming and models and data suggest that the Arctic is more sensitive to climatic change than other latitudes, anomalies associated with warm Arctic seasons have been studied.The regional temperature, precipitation and pressure anomalies in the northern hemisphere for the 10 warmest Arctic winters and 10 warmest Arctic summers during the last 70 years have been investigated. Even when the Arctic area is warm, there are circulation changes such that large coherent anomalies occur elsewhere, with some regions warming and some cooling. The 10 warmest Arctic winters were characterised by larger amplitude anomalies, in the Arctic and elsewhere, than the 10 warmest summers, illustrating the difference in response between seasons. The precipitation differences for the 10 warmest Arctic winters and summers show for North America large coherent areas of increase or decrease, which again differ according to season. However, in winter the differences are not statistically significant, while the differences in two areas are significant in summer.     

CO2 climate sensitivity and snow-sea-ice albedo parameterization in an atmospheric GCM coupled to a mixed-layer ocean model

The snow-sea-ice albedo parameterization in an atmospheric general circulation model (GCM), coupled to a simple mixed-layer ocean and run with an annual cycle of solar forcing, is altered from a version of the same model described by Washington and Meehl (1984). The model with the revised formulation is run to equilibrium for 1 × CO₂ and 2 × CO₂ experiments. The 1 ×CO₂ (control) simulation produces a global mean climate about 1° warmer than the original version, and sea-ice extent is reduced. The model with the altered parameterization displays heightened sensitivity in the global means, but the geographical patterns of climate change due to increased carbon dioxide (CO₂) are qualitatively similar. The magnitude of the climate change is affected, not only in areas directly influenced by snow and ice changes but also in other regions of the globe, including the tropics where sea-surface temperature, evaporation, and precipitation over the oceans are greater. With the less-sensitive formulation, the global mean surface air temperature increase is 3.5 °C, and the increase of global mean precipitation is 7.12%. The revised formulation produces a globally averaged surface air temperature increase of 4.04 °C and a precipitation increase of 7.25%, as well as greater warming of the upper tropical troposphere. Sensitivity of surface hydrology is qualitatively similar between the two cases with the larger-magnitude changes in the revised snow and ice-albedo scheme experiment. Variability of surface air temperature in the model is comparable to observations in most areas except at high latitudes during winter. In those regions, temporal variation of the sea-ice margin and fluctuations of snow cover dependent on the snow-ice-albedo formulation contribute to larger-than-observed temperature variability. This study highlights an uncertainty associated with results from current climate GCMs that use highly parameterized snow-sea-ice albedo schemes with simple mixed-layer ocean models.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.     

Characterizing the annual-mean climatic effect of anthropogenic CO<Subscript>2</Subscript> and aerosol emissions in eight coupled atmosphere-ocean GCMs

This work examines the spatial patterns of the transient response of mean annual temperature and precipitation to CO₂ (or CO₂ plus aerosol or aerosol proxy) radiative forcing in eight coupled AOGCMs, generally for the period 1900–2099. Response patterns are characterized using empirical orthogonal functions (EOFs) and the quasi-EOFs of Harvey and Wigley (the first qEOF field, discussed here, is given by the correlation between local year-by-year temperature changes and the global mean temperature change). The first temperature EOF accounts for 80–95% of the space-time variation of the CO₂ run in all of the models, and is almost identical to qEOF₁ of the temperature response or to the temperature change pattern averaged over the last 30 years of the simulations. EOF₁ accounts for 80–95% of the space-time variation in the CO₂+aerosol runs in six of the eight models. The CO₂ response patterns of different models are highly correlated with one another (R ² generally >0.5), and are also highly correlated with the CO₂+aerosol response patterns (R ² 0.85 in all except one model). The difference between CO₂ and CO₂+aerosol runs can be represented by EOF₁ of the year-by-year differences, by qEOF₁ of the year-by-year differences, or by the difference in temperature averaged over the last 30 years of each run. In models where these representations are highly correlated with each other, they are also highly correlated with CO₂ EOF₁. In other cases, aerosol EOF₁ is modestly to highly correlated with control EOF₁ (i.e.: the year-by-year differences between CO₂ and CO₂+aerosol runs are dominated by internal variability), while aerosol qEOF₁ and the 30-year difference are highly correlated with each other. For all models, the decadal mean temperature change can be closely replicated by scaling the CO₂ EOF₁ pattern based on the global mean temperature changes (RMSE for the last decade is <6% of the RMS temperature change for CO₂ runs, <8% for CO₂+aerosol runs). The first EOF of the precipitation response to increasing CO₂ accounts for only 10–30% of the space-time variation, and is generally highly correlated (R ² up to 0.85) with control EOF₁. In all of the models, there is an increase in precipitation in the ITCZ and a decrease in bands at or near 30°S and 30°N. In many models there is an El Niño-like response, including a substantial decrease in precipitation over the Amazon. Global-mean precipitation increases in all models due to CO₂ forcing, but aerosols appear to have a disproportionally large effect in suppressing the increase compared to their effect in suppressing the warming. There is evidence in some models that the non-absorbing aerosols considered here reduce summer monsoon rainfall compared to the changes that would be expected based on the globally averaged effect of aerosols on precipitation. When regional precipitation changes over time are predicted by scaling a fixed precipitation-change pattern with the global mean temperature change, the global mean RMSE in the predicted change in decadal-mean precipitation is 25–35% of the global RMS precipitation changes by the end of the simulation.