Search

The reliability of general circulation models (GCMs) is commonly associated with their ability to reproduce relevant aspects of observed climate, and thus the evaluation of GCM performance has become a standard practice for climate change studies. As such, there is an ever-growing literature that focuses on developing and evaluating metrics to assess GCM performance. In this paper it is shown that some commonly applied metrics provide little information for discriminating GCMs based on their performance, once uncertainty is included. A new methodology is proposed that differs from common approaches in that it focuses on evaluating GCMs' abilities to reproduce the observed response of surface temperature to changes in external radiative forcing (RF), while controlling for observed and simulated variability. It uses formal statistical tests to evaluate two aspects of the warming trend that are central for climate change studies: 1) if the response to RF produced by a particular GCM is compatible with observations and 2) if the magnitudes of the observed and simulated rates of warming are statistically similar. We illustrate the proposed methodology by evaluating the ability of 21 GCMs to reproduce the observed warming trend at the global scale and for eight subcontinental land domains. Results show that most of the GCMs provide an adequate representation of the observed warming trend for the global scale and for domains located in the Southern Hemisphere. However, GCMs tend to overestimate the warming rate for domains in the Northern Hemisphere, particularly since the mid-1990s. [ABSTRACT FROM AUTHOR]

The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP's precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies' preparation for future environmental challenges. Some key issues for future TP studies are also discussed. [ABSTRACT FROM AUTHOR]

A recent paper suggested that the global climate models used to project future climate changes may significantly overestimate the stability of the Atlantic meridional overturning circulation under anthropogenic global warming. It further asserted that "flux adjusting" the models (adding offsets to heat and freshwater fluxes to reproduce the observed density field) may reduce model stability. However, temperature, salinity, and density fields in climate models likely deviate from observations because of biases in model physics as well as inaccuracies in fluxes. In such cases it is unclear whether adjusting the fluxes to produce a more realistic density field will result in a model with more realistic stability properties, as flux correction may be compensating for other inaccuracies in model formulation. We investigate this question using a simplified dynamical box model, in which we can flux correct one version of the model to match density gradients within another version of the model. We show that flux adjustment can realistically compensate for biases in stability associated with some processes, such as uncertainty in the value of the vertical diffusivity, but not other processes, such as inaccurate simulation of the relationship between density structure and overturning or the isopycnal tracer diffusivity coefficient. An ability to compensate for biases when the overturning shuts off does not imply an ability to compensate for biases in when it reestablishes itself, and vice versa. [ABSTRACT FROM AUTHOR]

This paper mainly addresses two issues that concern the longwave climate feedbacks. First, it is recognized that the radiative forcing of greenhouse gases, as measured by their impact on the outgoing longwave radiation (OLR), may vary across different climate models even when the concentrations of these gases are identically prescribed. This forcing variation contributes to the discrepancy in these models' projections of surface warming. A method is proposed to account for this effect in diagnosing the sensitivity and feedbacks in the models. Second, it is shown that the stratosphere is an important factor that affects the OLR in transient climate change. Stratospheric water vapor and temperature changes may both act as a positive feedback mechanism during global warming and cannot be fully accounted as a 'stratospheric adjustment' of radiative forcing. Neglecting these two issues may cause a bias in the longwave cloud feedback diagnosed as a residual term in the decomposition of OLR variations. There is no consensus among the climate models on the sign of the longwave cloud feedback after accounting for both issues. [ABSTRACT FROM AUTHOR]

This paper improves an extreme-value-theory-based detection and attribution method and then applies it to four types of extreme temperatures, annual minimum daily minimum (TNn) and maximum (TXn) and annual maximum daily minimum (TNx) and maximum (TXx), using the HadEX2 observation and the CMIP5 multimodel simulation datasets of the period 1951-2010 at 17 subcontinent regions. The methodology is an analog of the fingerprinting method adapted to extremes using the generalized extreme value (GEV) distribution. The signals are estimated as the time-dependent location parameters of GEV distributions fitted to extremes simulated by multimodel ensembles under anthropogenic (ANT), natural (NAT), or combined anthropogenic and natural (ALL) external forcings. The observed extremes are modeled by GEV distributions whose location parameters incorporate the signals as covariates. A coordinate descent algorithm improves both computational efficiency and accuracy in comparison to the existing method, facilitating detection of multiple signals simultaneously. An overall goodness-of-fit test was performed at the regional level. The ANT signal was separated from the NAT signal in four to six regions. In these analyses, the waiting times of the 1951-55 20-yr return level in the 2006-10 climate for the temperature of the coldest night and day were found to have increased to over 20 yr; the corresponding waiting times for the warmest night and day were found to have dropped below 20 yr in a majority of the regions. [ABSTRACT FROM AUTHOR]

The role of stationary planetary waves in the dynamical response of the Arctic winter stratosphere circulation to global warming is investigated here by analyzing simulations performed with atmosphere-only models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) driven by prescribed sea surface temperatures (SSTs). Climate models often simulate dynamical warming of the Arctic stratosphere as a response to global warming in association with a strengthening of the deep branch of the Brewer-Dobson circulation; however, until now, no satisfactory mechanism for such a response has been suggested. This study focuses on December-February (DJF) because this is the period when the troposphere and stratosphere are strongly coupled. When forced by increased SSTs, all the models analyzed here simulate Arctic stratosphere dynamical warming, mostly due to increased upward propagation of quasi-stationary wavenumber 1, as diagnosed by the meridional eddy heat flux. Further, it is shown that the stratospheric warming and increased wave flux to the stratosphere are related to the strengthening of the zonal winds in subtropics and midlatitudes near the tropopause. Evidence presented in this paper corroborate climate model simulations of future stratospheric changes and suggest a dynamical warming of the Arctic polar vortex as the most likely response to global warming. [ABSTRACT FROM AUTHOR]

Large temperature variations in a temperate climate, particularly in late winter and early spring, can be disruptive for native ecosystems and agricultural crops. As warmer temperatures occur earlier in the year in midlatitude regions as a result of anthropogenic climate change, springtime temperatures may become less consistent, leading to potential damage to species and crops that are vulnerable to the return of historically cooler temperatures, including late-spring frosts, after an initial warm-up. In this work, we quantify shifting patterns in late-winter and springtime temperature variations at eight sites across New Jersey from 1950 to 2019. Many sites located along the coast or in the coastal plain experience increases in the number of times the temperature climbs above 15.5°C (60°F) and then falls below freezing (i.e.,0°C, or 32°F). Sites in southern New Jersey (where much of the state's agriculture is located) experience the most significant (P < 0.05) increases in large springtime temperature variations. Across all sites, there is a general increase in both the percentage and magnitude of temperature variations that occur as early as February. At 75% of sites, day-to-day variation in daily maximum temperature has increased from the 1950s through 2019; day-to-day variation in daily minimum temperatures has increased over the same time at more than half of sites considered. These amplifications in extreme temperature variations indicate the need for both mitigation and adaptation strategies to protect vulnerable crops and ecosystems in the region during this critical time of the year. Significance Statement: Human-caused climate change has made it more likely for warmer temperatures to occur earlier in the year, causing many locations to experience late-winter and early-springtime temperatures that are less consistent than they may have been in the past. These variations can be highly problematic for both vital agricultural crops and critical ecosystems. Here, we evaluate how late-winter and early-springtime temperatures have changed throughout New Jersey (home to a variety of agriculture and unique ecosystems) from the mid-twentieth century until 2019. We find critical changes to temperature patterns during late winter and early spring, including larger and more frequent temperature swings (particularly in February) and increased day-to-day variation in high and low temperatures. [ABSTRACT FROM AUTHOR]

Recent observations and model studies of the earth’s radiative energy balance have focused attention on the earth’s top of atmosphere (TOA) energy balance. This is the balance between the shortwave energy absorbed by the earth, which is represented by a spatially and temporally averaged absorbed flux , and the emitted longwave energy, which is represented by the corresponding averaged emitted flux . The TOA average net flux FN is defined as the difference between the two over the averaged area and time, which may be a local, regional, or global average. A global nonzero net flux represents a measure of imbalance between the energy being absorbed and emitted by the earth for the time interval in question. It is of interest to ask what the natural variability of the net flux might be and whether, during times of climate change, signals of important climate change processes might be detected against this natural background variation; examples of these signals include evidence of ocean heat storage, the effects of El Niño, and the radiative effects of volcanic eruptions. In this paper, the authors review the significance of the net flux, survey the observational evidence from a range of satellite instruments over several decades, and analyze some of the most recent observations from the Clouds and the Earth’s Radiant Energy System (CERES) program to determine what signals and what natural variability might be expected in the TOA net flux. Based on this analysis, the use of broadband radiation measurements for global climate change studies can be assessed. [ABSTRACT FROM AUTHOR]

This paper describes a new version of the University of Washington shallow cumulus parameterization. The new version includes improved treatments of lateral mixing rates into cumulus updrafts, the evaporation of precipitation and of the interaction of cumuli with the underlying subcloud layer, and a treatment of the convective inhibition-based mass-flux closure that is more numerically stable and is suitable for the long time steps of global climate models. The paper also documents its performance when combined with a new moist turbulence parameterization in simulations with version 3.5 of the Community Atmosphere Model (CAM3.5). A single-column simulation of nonprecipitating trade cumulus shows considerable improvements in vertical thermodynamic structure and less resolution sensitivity in the new schemes compared to CAM3.5. In global simulations, the new schemes, combined with an increase of vertical resolution from 26 to 30 levels, produce a significant (7%) reduction in overall climate bias, calculated from root-mean-squared error of the seasonal model climatology compared to a suite of global observations of various fields. Biases in almost all fields, particularly the shortwave cloud radiative forcing, are reduced. Geographical bias patterns in surface rainfall, liquid water path, and surface air temperature are only mildly affected by the model parameterization and vertical resolution changes. [ABSTRACT FROM AUTHOR]

The dominant interannual El Niño–Southern Oscillation (ENSO) phenomenon and the short length of climate observation records make it difficult to study long-term climate variations in the spatiotemporal domain. Based on the fact that the ENSO signal spreads to remote regions and induces delayed climate variation through atmospheric teleconnections, an ENSO-removal method is developed through which the ENSO signal can be approximately removed at the grid box level from the spatiotemporal field of a climate parameter. After this signal is removed, long-term climate variations are isolated at mid- and low latitudes in the climate parameter fields from observed and reanalysis datasets. This paper addresses the long-term global warming trend (GW); a companion paper concentrates on Pacific pan-decadal variability (PDV). The warming that occurs in the Pacific basin (approximately 0.4 K in the twentieth century) is much weaker than in surrounding regions and the other two ocean basins (approximately 0.8 K). The modest warming in the Pacific basin is likely due to its dynamic nature on the interannual and decadal time scales and/or the leakage of upper ocean water through the Indonesian Throughflow. Based on the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), a comprehensive atmospheric structure associated with the GW trend is given. Significant discrepancies exist between the two datasets, especially in the tightly coupled dynamics and water vapor fields. The dynamics fields based on NCEP–NCAR, which show a change in the Walker Circulation, are consistent with the GW change in the surface temperature field. However, intensification in the Hadley Circulation is associated with GW trend in ERA-40 instead. [ABSTRACT FROM AUTHOR]

The potential role of the impacts of land-cover changes (LCCs) in the Australian climate is investigated within the context of increasing CO2 concentrations and temperature. Specifically, it is explored if possible scenarios for LCC can moderate or amplify CO2-induced changes in climate over Australia. The January climate of Australia is simulated under three different land-cover-change scenarios using a high-resolution regional climate model. The land-cover-change scenarios include a steady-state land cover that is equivalent to current land cover, a low-reforestation scenario that recovers approximately 25% of the trees replaced by grasslands within the last 200 yr, and a high-reforestation scenario that recovers at least 75% of the deforested regions. The model was driven by boundary conditions taken from transitory climate simulations from a general circulation model that included two climate scenarios based on two projected scenarios of CO2 concentration increase. The results show that reforestation has the potential to reduce the projected increase in Australian temperatures in 2050 and 2100 by as much as 40% and 20%, respectively. This cooling effect, however, is highly localized and occurs only in regions of reforestation. The results therefore hint that the potential of reforestation to moderate the impact of global warming may be significantly limited by the spatial scale of reforestation. In terms of deforestation, results show that any future land clearing can exacerbate the projected warming in certain regions of Australia. Carbon-related variables are also analyzed and results show that changes in net CO2 flux may be influenced more by soil respiration than by photosynthesis. The results herein encourage studies on the inclusion of land-cover-change scenarios in future climate change projection simulations of the Australian climate. [ABSTRACT FROM AUTHOR]

A currently popular idea is that El Niño–Southern Oscillation (ENSO) can be viewed as a linear deterministic system forced by noise representing processes with periods shorter than ENSO. Also, there is observational evidence to suggest that the Madden–Julian oscillation (MJO) acts to trigger and/or amplify the warm phase of ENSO in this way. The feedback of the slower process, ENSO, to higher-frequency atmospheric phenomena, of which a large part of the variability in the intraseasonal band is due to the MJO, has received little attention. This paper considers the hypothesis that the probability of an El Niño event is modified by high MJO activity and that, in turn, the MJO is regulated by ENSO activity. If this is indeed the case, then viewing ENSO as a low-frequency oscillation forced by additive stochastic noise would not present a complete picture. This paper tests the above hypothesis using a stochastically forced intermediate coupled model by allowing ENSO to directly influence the stochastic forcing. The model response to a variety of stochastic forcing types is found to be sensitive to the type of forcing applied. When the model is operated beyond its intrinsic Hopf bifurcation, its probability distribution function (PDF) is fundamentally altered when the stochastic forcing is changed from additive to multiplicative. The model integration period also influences the shape of the PDF, which is also compared to the PDF derived from observations. It is found that multiplicative stochastic forcing reproduces some measures of the observations better than the additive stochastic forcing. [ABSTRACT FROM AUTHOR]

Global climate model simulations project that the tropical Andes Mountains of South America, which are particularly vulnerable to climate change because of a reliance on snow and glacial melt for freshwater resources, will experience enhanced warming in the near future, with both higher rates of warming at higher elevations within the mountain range itself and localized enhancement of warming exceeding surrounding areas of the globe. Yet recent surface temperature changes in the tropical Andes do not show evidence for either elevation-dependent warming or regional enhancement of warming on average. However, it remains a possibility that the expected warming trends in this region have begun to manifest in other ways (e.g., in the free atmosphere or at intermediate mountain elevations). This paper proposes evidence from several reanalysis products that there has indeed been a regional enhancement of midtropospheric warming around the central Andes over the past few decades that makes this region stand out as a hot spot within the broader pantropics. This trend is generally not reproduced by historical AMIP climate model simulations, which suggests that the mechanisms through which the atmosphere is warming over the central Andes are not adequately captured by climate models. Possible explanations for localized enhancement of warming in this region are considered. On the other hand, reanalysis products do not consistently exhibit enhanced warming at intermediate mountain elevations in the central Andes as evidenced by the generally moderate rates of change in the freezing-level height, except perhaps in the highest-resolution reanalysis product. [ABSTRACT FROM AUTHOR]

This paper investigates changes in the tropical tropopause layer (TTL) in response to carbon dioxide increase and surface warming separately in an atmospheric general circulation model, finding that both effects lead to a warmer tropical tropopause. Surface warming also results in an upward shift of the tropopause. A detailed heat budget analysis is performed to quantify the contributions from different radiative and dynamic processes to changes in the TTL temperature. When carbon dioxide increases with fixed surface temperature, a warmer TTL mainly results from the direct radiative effect of carbon dioxide increase. With surface warming, the largest contribution to the TTL warming comes from the radiative effect of the warmer troposphere, which is partly canceled by the radiative effect of the moistening at the TTL. Strengthening of the stratospheric circulation following surface warming cools the lower stratosphere dynamically and radiatively via changes in ozone. These two effects are of comparable magnitudes. This circulation change is the main cause of temperature changes near 63 hPa but is weak near 100 hPa. Contributions from changes in convection and clouds are also quantified. These results illustrate the heat budget analysis as a useful tool to disentangle the radiative-dynamical-chemical-convective coupling at the TTL and to facilitate an understanding of intermodel difference. [ABSTRACT FROM AUTHOR]

Large-scale synoptic circulations have a profound effect on western U.S. summer weather and climate. Heat waves, water availability, the distribution of monsoonal moisture, fire-weather conditions, and other phenomena are impacted by the position and amplitude of large-scale synoptic circulations. Furthermore, regional weather is modulated by the interactions of the large-scale flow with terrain and land-water contrasts. It is therefore crucial to understand projected changes in large-scale circulations and their variability under anthropogenic global warming. Although recent research has examined changes in the jet stream, storm tracks, and synoptic disturbances over the Northern Hemisphere under global warming, most papers have focused on the cold season. In contrast, this work analyzes the projected trends in the spatial distribution and amplitude of large-scale synoptic disturbances over the western United States and eastern Pacific during July and August. It is shown that CMIP5 models project weaker mean midtropospheric gradients in geopotential height as well as attenuated temporal variability in geopotential height, temperature, vorticity, vertical motion, and sea level pressure over this region. Most models suggest reduced frequency of troughs and increased frequency of ridges over the western United States. These changes in the variability of synoptic disturbances have substantial implications for future regional weather and climate. [ABSTRACT FROM AUTHOR]

How will warming temperatures influence thunderstorm severity? This question can be explored by using climate models to diagnose changes in large-scale convective instability (CAPE) and wind shear, conditions that are known to be conducive to the formation of severe thunderstorms. First, an ensemble of climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) is evaluated on its ability to reproduce a radiosonde climatology of such storm-favorable conditions in the current climate's spring and summer seasons, focusing on the contiguous United States (CONUS). Of the 11 climate models evaluated, a high-performing subset of four (GFDL CM3, GFDL-ESM2M, MRI-CGCM3, and NorESM1-M) is identified. Second, the twenty-first-century changes in the frequency of environments favorable to severe thunderstorms are calculated in these high-performing models as they are forced by the RCP4.5 and RCP8.5 emissions pathways. For the RCP8.5 scenario, the models predict consistent CONUS-mean fractional springtime increases in the range of 50%-180% by the end of the twenty-first century; for the summer, three of the four models predict increases in the range of 40%-120% and one model predicts a small decrease. This disagreement between the models is traced to divergent projections for future CAPE and boundary layer humidity in the Great Plains. This paper also explores the sensitivity of the results to the relative weight given to wind shear in determining how 'favorable' a large-scale environment is for the development of severe thunderstorms, and it is found that this weighting is not the dominant source of uncertainty in projections of future thunderstorm severity. [ABSTRACT FROM AUTHOR]

Derechos are extensive swaths of damaging winds produced by some long-lived, widespread mesoscale convective systems. Little research has been conducted concerning how derecho mechanisms might change in a future, warmer climate. In this study, the pseudo–global warming method is utilized to evaluate how the 10 August 2020 midwestern U.S. derecho, the costliest thunderstorm event in U.S. history to date, might differ if it instead occurred in a warmer climate at the end of this century. The 10 August derecho event is first simulated in its observed environment, and then resimulated in environments altered according to projections from different climate models using a high-emissions climate change scenario. Results suggest that near the end of this century, a similar derecho event may not necessarily have more intense winds but could possibly impact a geographical area 50% to 100% larger. The physical chain of events leading to this greater geographical impact result from the derecho winds beginning earlier in the storm lifetime, due to increased precipitation combined with decreased relative humidity right above the ground, and derecho winds extending northward due to a strengthening of the parent storm from increased instability there. All these factors enhance the area of evaporative cooling and thus the cold pool, which in turn extends the area covered by the rear-inflow jet within the storm, the likely main mechanism for most of the damaging winds at the ground in the historical event. More study of other cases is required to evaluate the generality of this result. [ABSTRACT FROM AUTHOR]

This study investigated the uncertainty involved in statistical downscaling of hydroclimatic time series obtained by artificial neural networks (ANNs). Phase 6 of the Coupled Model Intercomparison Project (CMIP6) general circulation model (GCM) Canadian Earth System Model, version 5 (CanESM5), was used as large-scale predictor data for downscaling temperature and precipitation parameters. Two ANNs, feed forward and long short-term memory (LSTM), were utilized for statistical downscaling. To quantify the uncertainty of downscaling, prediction intervals (PIs) were estimated via the lower upper bound estimation (LUBE) method. To assess performance of proposed models in different climate regimes, data from the Tabriz and Rasht stations in Iran were employed. The calibrated models via historical GCM data were used for future projections via the high-forcing and fossil fuel–driven development scenario shared socioeconomic pathway (SSP) 5-8.5. Projections were compared with the Canadian Regional Climate Model 4 (Can-RCM4) projections via the same scenario. Results indicated that both LSTM-based point predictions and PIs are more accurate than the feedforward neural network (FFNN)-based predictions, with an average of 55% higher Nash–Sutcliffe efficiency (NSE) for point predictions and 25% lower coverage width criterion (CWC) for PIs. Projections suggested that Tabriz is going to experience a warmer climate with an increase in average temperature of 2° and 5°C for near and far futures, respectively, and a drier climate with a 20% decrease in precipitation until 2100. Future projections for the Rasht station, however, suggested a more uniform climate with less seasonal variability. Average precipitation will increase by up to 25% and 70% until near and far future periods, respectively. Ultimately, point predictions show that the average temperature in Rasht will increase by 1°C until the near future and then be a constant average temperature until the far future. Significance Statement: The downscaling of hydroclimatic parameters is subject to uncertainty. The best way is to provide an area with the highest contingency of them as a prediction interval. The reduction width of such an interval leads to increased confidence in explaining and predicting these processes. We proposed and applied a deep learning–based machine learning method for both point prediction and prediction interval estimation of temperature and precipitation parameters for the future over two different climatic regions. The results show the superiority of such a machine learning–based prediction interval estimation for quantification of the downscaling uncertainty. [ABSTRACT FROM AUTHOR]

Global warming has been accelerating the frequency and intensity of climate extremes, and has had an immense influence on the economy and society, but attention is seldom paid to future Antarctic temperature extremes. This study investigates five surface extreme temperature indices derived from the multimodel ensemble mean (MMEM) based on 14 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) under the shared socioeconomic pathways (SSPs) of SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. In Antarctica, the variations in extreme temperature indices exhibit regional and seasonal differences. The diurnal temperature range (DTR) usually illustrates a downward trend, particularly for the Antarctic Peninsula and Antarctic coast, and the strongest change occurs in austral summer. In all cases, the annual highest minimum/maximum temperature (TNx/TXx) increases faster in inland Antarctica. Antarctic amplification of extreme temperature indices is detected and is strongest at the lowest maximum temperature (TXn). At the Antarctic Peninsula, TXx amplification only appears in winter. Great DTR amplification appears along the Antarctic coast and is strongest in summer and weakest in winter. The changes in extreme temperature indices indicate the accelerated Antarctic warming in future scenarios. [ABSTRACT FROM AUTHOR]

The importance of investigating regional climate changes associated with degrees of global warming is increasingly being recognized, but the majority of relevant research has been based on multimodel ensembles (MMEs) from the Coupled Model Intercomparison Project (CMIP). This has left two important questions unanswered: Are there plausible futures which are not represented by the models in CMIP? And, how would regional climates evolve under enhanced global warming, beyond 4°C? In this paper, two perturbed physics ensembles (PPEs) are used to address these issues with reference to African precipitation. Examination of model versions that generate warming greater than 4°C in the twenty-first century shows that changes in African precipitation are enhanced gradually, even to high global temperatures; however, there may be nonlinearities that are not incorporated here due to limited model complexity. The range of projections from the PPEs is compared to data from phases 3 and 5 of CMIP (CMIP3 and CMIP5), revealing regional differences. This is partly the result of implausible model versions, but the PPE dataset can be justifiably constrained given its size and systematic nature, highlighting an additional advantage over MMEs. After applying constraints, the PPEs still show changes that are outside the range of CMIP, most prominently strong dry signals in west equatorial Africa and the Sahel, implying that MMEs may underestimate risks for these regions. Analysis of African precipitation changes therefore demonstrates that regional assessments that rely on CMIP3 and CMIP5 may overlook uncertainties associated with model parameterizations and pronounced warming. More systematic approaches are needed for conservative estimates of danger. [ABSTRACT FROM AUTHOR]

The change in predictability of monthly mean temperature in a future climate is quantified based on the Community Climate System Model, version 4. According to this model, the North Atlantic overtakes the El Niño-Southern Oscillation (ENSO) as the dominant area of seasonal predictability by 2095. This change arises partly because ENSO becomes less variable and partly because the ENSO teleconnection pattern expands into the Atlantic. Over land, the largest change in temperature predictability occurs in the tropics and is predominantly due to a decrease in ENSO variability. The southern peninsula of Africa and northeast South America are predicted to experience significant drying in a future climate, which decreases the effective heat capacity and memory, and hence increases variance independently of ENSO changes. Extratropical land areas experience enhanced precipitation in a future climate, which decreases temperature variance by the same mechanism. Finally, the model predicts that surface temperatures near the poles will become more predictable and less variable in a future climate, primarily because melting sea ice exposes the underlying sea surface temperature, which is more predictable owing to its longer time scale. Some of these results, especially the change in ENSO variance, are known to be model dependent. This paper also advances the use of information theory to quantify predictability, including 1) deriving a quantitative relation between predictability of the first and second kinds; 2) showing how differences in predictability can be decomposed in two dramatically different ways, facilitating physical interpretation; and 3) proposing a sample estimate of mutual information whose significance can be tested using standard techniques. [ABSTRACT FROM AUTHOR]

The impacts of absorbing aerosols on global climate are not completely understood. This paper presents the results of idealized experiments conducted with the Community Atmosphere Model, version 4 (CAM4), coupled to a slab ocean model (CAM4-SOM) to simulate the climate response to increases in tropospheric black carbon aerosols (BC) by direct and semidirect effects. CAM4-SOM was forced with 0, 1×, 2×, 5×, and 10× an estimate of the present day concentration of BC while maintaining the estimated present day global spatial and vertical distribution. The top-of-atmosphere (TOA) radiative forcing of BC in these experiments is positive (warming) and increases linearly as the BC burden increases. The total semidirect effect for the 1 × BC experiment is positive but becomes increasingly negative for higher BC concentrations. The global-average surface temperature response is found to be a linear function of the TOA radiative forcing. The climate sensitivity to BC from these experiments is estimated to be 0.42 K W−1 m2 when the semidirect effects are accounted for and 0.22 K W−1 m2 with only the direct effects considered. Global-average precipitation decreases linearly as BC increases, with a precipitation sensitivity to atmospheric absorption of 0.4% W−1 m2. The hemispheric asymmetry of BC also causes an increase in southward cross-equatorial heat transport and a resulting northward shift of the intertropical convergence zone in the simulations at a rate of 4° PW−1. Global-average mid- and high-level clouds decrease, whereas the low-level clouds increase linearly with BC. The increase in marine stratocumulus cloud fraction over the southern tropical Atlantic is caused by increased BC-induced diabatic heating of the free troposphere. [ABSTRACT FROM AUTHOR]

Global warming will have direct impacts on regional water resources by accelerating the hydrological cycle. Hydrological simulation is an important approach to studying climate change impacts. In this paper, a snowmelt-based water balance model (SWBM) was used to simulate the effect of climate change on runoff in the Kuye River catchment of the Loess Plateau, China. Results indicated that the SWBM is suitable for simulating monthly discharge into arid catchments. The response of runoff in the Kuye River catchment to climate change is nonlinear, and runoff is more sensitive to changes in precipitation than to changes in temperature. The projections indicated that the Kuye River catchment would undergo more flooding in the 2020s, and global warming would probably shorten the main flood season in the catchment, with greater discharge occurring in August. Although projected changes in annual runoff are uncertain, the possibilities of regional water shortages and regional flooding are essential issues that need to be fully considered. [ABSTRACT FROM AUTHOR]

The response over West Africa to uniform warming of the Atlantic Ocean is analyzed using idealized simulations with a regional climate model. With warming of 1 and 1.5 K, rainfall rates increase by 30%-50% over most of West Africa. With Atlantic warming of 2 K and higher, coastal precipitation increases but Sahel rainfall decreases substantially. This nonlinear response in Sahel rainfall is the focus of this analysis. Atlantic warming is accompanied by decreases in low-level geopotential heights in the Gulf of Guinea and in the large-scale meridional geopotential height gradient. This leads to easterly wind anomalies in the central Sahel. With Atlantic warming below 2 K, these easterly anomalies support moisture transport from the Gulf of Guinea and precipitation increases. With Atlantic warming over 2 K, the easterly anomalies reverse the westerly flow over the Sahel. The resulting dry air advection into the Sahel reduces precipitation. Increased low-level moisture provides moist static energy to initiate convection with Atlantic warming at 1.5 K and below, while decreased moisture and stable thermal profiles suppress convection with additional warming. In all simulations, the southerly monsoon flow onto the Guinean coast is maintained and precipitation in that region increases. The relevance of these results to the global warming problem is limited by the focus on Atlantic warming alone. However, confident prediction of climate change requires an understanding of the physical processes of change, and this paper contributes to that goal. [ABSTRACT FROM AUTHOR]

Constraining the low-frequency (LF) behavior of general circulation models (GCMs) requires reliable observational estimates of LF variability. This two-part paper presents multiproxy reconstructions of Niño-3.4 sea surface temperature over the last millennium, applying two techniques [composite plus scale (CPS) and hybrid regularized expectation maximization (RegEM) truncated total least squares (TTLS)] to a network of tropical, high-resolution proxy records. This first part presents the data and methodology before evaluating their predictive skill using frozen network analysis (FNA) and pseudoproxy experiments. The FNA results suggest that about half of the Niño-3.4 variance can be reconstructed back to A.D. 1000, but they show little LF skill during certain intervals. More variance can be reconstructed in the interannual band where climate signals are strongest, but this band is affected by dating uncertainties (which are not formally addressed here). The CPS reliably estimates interannual variability, while LF fluctuations are more faithfully reconstructed with RegEM, albeit with inevitable variance loss. The RegEM approach is also tested on representative pseudoproxy networks derived from two millennium-long integrations of a coupled GCM. The pseudoproxy study confirms that reconstruction skill is significant in both the interannual and LF bands, provided that sufficient variance is exhibited in the target Niño-3.4 index. It also suggests that FNA severely underestimates LF skill, even when LF variability is strong, resulting in overly pessimistic performance assessments. The centennial-scale variance of the historical Niño-3.4 index falls somewhere between the two model simulations, suggesting that the network and methodology presented here would be able to capture the leading LF variations in Niño-3.4 for much of the past millennium, with the caveats noted above. [ABSTRACT FROM AUTHOR]

This paper diagnoses the temperature trends in maximum ( Tmax) and minimum temperatures ( Tmin) over a selection of 65 stations spread over the southeast United States (SEUS) from three observed datasets. They are the Cooperative Observer network program (COOP), the COOP data corrected for documented shifts in time of observation (COOP1), and the COOP data additionally corrected for documented changes in instrumentation (COOP2). These 65 stations have been isolated for having the three observed datasets for the same time period from 1948 to 2009. The authors' comparisons suggest that COOP2 displays stronger warming (cooling) trends in Tmax ( Tmin) compared with COOP1 in all four seasons. This is consistent with the expectation from the bias correction applied for the instrument change. In comparison, the differences between COOP and COOP2 are relatively larger. In the spring, summer, and fall seasons, the median Tmax trend is warming in COOP2 while it is cooling in COOP. In the winter season, the median trends of Tmax in the two datasets are positive, but their magnitudes are substantially different. Similarly, in the winter, summer, and fall seasons, the warming trend in Tmin in COOP is contrary to the cooling trend in COOP2. In the spring season, the median trend in Tmin is comparable between the two datasets. COOP2 shows the relationship of trends in Tmin, with the extent of urbanization in these 65 stations, to be statistically significant and to be consistent with expectations from theory in contrast to the COOP data. [ABSTRACT FROM AUTHOR]

Recently Diem questioned the western ridge movement of the North Atlantic subtropical high (NASH) reported in a 2011 paper of Li et al. This reply shows more analysis that further strengthens the conclusions originally put forth by Li et al. Diem''s analysis of the trend in the western ridge of the NASH was based on the data over a 30-yr period (1978-2007), whereas the main conclusions in Li et al. were drawn according to the data over a 60-yr period (1948-2007). Over the last 60 years, the NASH has shown a significant trend of westward movement, the meridional movement of the western ridge of the NASH has enhanced in the recent three decades, and the potential impact of global warming cannot be ruled out in an attempt to explain these changes of the NASH. [ABSTRACT FROM AUTHOR]

Impacts of climate change on agriculture are a major concern worldwide, but uncertainties of climate models and emission scenarios may hamper efforts to adapt to climate change. In this paper, a probabilistic approach is used to estimate the uncertainties and simulate impacts of global warming on wheat production and water use in the main wheat cultivation regions of China, with a global mean temperature (GMT) increase scale relative to 1961-90 values. From output of 20 climate scenarios of the Intergovernmental Panel on Climate Change Data Distribution Centre, median values of projected changes in monthly mean climate variables for representative stations are adapted. These are used to drive the Crop Environment Resource Synthesis (CERES)-Wheat model to simulate wheat production and water use under baseline and global warming scenarios, with and without consideration of carbon dioxide (CO2) fertilization effects. Results show that, because of temperature increase, projected wheat-growing periods for GMT changes of 1°, 2°, and 3°C would shorten, with averaged median values of 3.94%, 6.90%, and 9.67%, respectively. There is a high probability of decreasing (increasing) changes in yield and water-use efficiency under higher temperature scenarios without (with) consideration of CO2 fertilization effects. Elevated CO2 concentration generally compensates for the negative effects of warming temperatures on production. Moreover, positive effects of elevated CO2 concentration on grain yield increase with warming temperatures. The findings could be critical for climate-change-driven agricultural production that ensures global food security. [ABSTRACT FROM AUTHOR]

Recent heightened concern regarding possible consequences of anthropogenically induced global warming has spurred analyses of data aimed at detection of climate change and more thorough characterization of the natural climate variability. However, there is greater concern regarding the extent and especially quality of the historical climate data. In this paper, rainfall records of 233 gauge stations over Ethiopia for the 1978-2007 period are employed in an analysis that involves homogenization, reconstruction, and gridding onto a regular 0.5° × 0.5° resolution grid. Inhomogeneity is detected and adjusted based on quantile matching. The regularized expectation-maximization and multichannel singular spectrum analysis algorithms are then utilized for imputation of missing values, and the latter has been determined to have a marginal advantage. Ordinary kriging is used to create a gridded monthly rainfall dataset. The spatial and temporal coherence of this dataset are assessed using harmonic analysis, self-organizing maps, and intercomparison with global datasets. The self-organizing map delineates Ethiopia into nine homogeneous rainfall regimes, which is consistent with seasonal and interannual rainfall variations. The harmonic analysis of the dataset reveals that the annual mode accounts for 55%-85% of the seasonal rainfall variability over western Ethiopia while the semiannual mode accounts for up to 40% over southern Ethiopia. The dataset is also intercompared with Global Precipitation Climatology Project (GPCP), Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), Climatic Research Unit time series version 3 (CRUTS3.0), Tropical Rainfall Measuring Mission (TRMM), and interim ECMWF Re-Analysis (ERA-Interim) rainfall. The correlation of the dataset with global datasets ranges from 0.52 to 0.95 over sparse to dense rain gauge regions. The GPCP rainfall has a small bias and good correlation with the new dataset whereas TRMM and ERA-Interim have relatively large dry and wet biases, respectively. [ABSTRACT FROM AUTHOR]

Climate change is expected to accelerate the hydrologic cycle, increase the fraction of precipitation that is rain, and enhance snowpack melting. The enhanced hydrological cycle is also expected to increase snowfall amounts due to increased moisture availability. These processes are examined in this paper in the Colorado Headwaters region through the use of a coupled high-resolution climate--runoff model. Four high-resolution simulations of annual snowfall over Colorado are conducted. The simulations are verified using Snowpack Telemetry (SNOTEL) data. Results are then presented regarding the grid spacing needed for appropriate simulation of snowfall. Finally, climate sensitivity is explored using a pseudo--global warming approach. The results show that the proper spatial and temporal depiction of snowfall adequate for water resource and climate change purposes can be achieved with the appropriate choice of model grid spacing and parameterizations. The pseudo--global warming simulations indicate enhanced snowfall on the order of 10%%--25%% over the Colorado Headwaters region, with the enhancement being less in the core headwaters region due to the topographic reduction of precipitation upstream of the region (rain-shadow effect). The main climate change impacts are in the enhanced melting at the lower-elevation bound of the snowpack and the increased snowfall at higher elevations. The changes in peak snow mass are generally near zero due to these two compensating effects, and simulated wintertime total runoff is above current levels. The 1 April snow water equivalent (SWE) is reduced by 25%% in the warmer climate, and the date of maximum SWE occurs 2--17 days prior to current climate results, consistent with previous studies. [ABSTRACT FROM AUTHOR]

Observations have indicated a trend of freshwater loss in the global western boundary current extension regions over several recent decades. In this paper, the coupled ocean--atmosphere response to the observed freshwater flux trend [[defined as evaporation minus precipitation (EmP)]] over the Kuroshio--Oyashio Extension (KOE) region is studied in a series of coupled model experiments. The model explicitly demonstrates that the positive EmP forcing in the KOE region can set up a cyclonic gyre straddling the subtropical and the subpolar gyre, which induces anomalous southward cold advection in the west and northward warm advection in the interior. This leads to the formation of a temperature dipole in the midlatitudes with a cooling in the west and a warming in the east. With the positive EmP forcing in the KOE, the response of the extratropical atmospheric circulation in the North Pacific sector is characterized by an equivalent barotropic low originating primarily from the western tropical Pacific changes and countered by the extratropical SST forcing. The positive EmP forcing also strengthens the tropical zonal SST gradient and thus ENSO through several competing processes including the surface-coupled wind--evaporative--SST (WES) mechanism, subduction of extratropical warm anomalies, and spinup of the density-driven meridional overturning circulation. Applications to recent Pacific climate changes are discussed. [ABSTRACT FROM AUTHOR]

Optically thin cirrus play a key role in the earth’s radiation budget and global climate change. Their radiative effects depend critically on the thin cirrus optical and microphysical properties. In this paper, inhomogeneous hexagonal monocrystals (IHMs), which consist of a pure hexagon with spherical air bubble or aerosol inclusions, are applied to calculate the single-scattering properties of individual ice crystals. The multiangular polarized characteristics of optically thin cirrus for the 0.865- and 1.38- μm spectral bands are simulated on the basis of an adding–doubling radiative transfer program. The sensitivity of total and polarized reflectance at the top of the atmosphere (TOA) to different aerosol, cirrus, and surface parameters is studied. A new sensitivity index is introduced to further quantify the sensitivity study. The TOA polarized reflectance measured by the Polarization and Directionality of the Earth’s Reflectance (POLDER) instruments is compared to simulated TOA total and polarized reflectance. The test results are reasonable, although small deviations caused by the change of aerosol properties and thin cirrus optical thickness do exist. Finally, on the basis of the sensitivity study, a conceptual approach is suggested to simultaneously retrieve thin cirrus clouds’ optical thickness, ice particle shape, and the underlying aerosol optical thickness using the TOA total and polarized reflectance of the 0.865- and 1.38- μm spectral bands measured at multiple viewing angles. [ABSTRACT FROM AUTHOR]

Perturbations to the carbon cycle could constitute large feedbacks on future changes in atmospheric CO2 concentration and climate. This paper demonstrates how carbon cycle feedback can be expressed in formally similar ways to climate feedback, and thus compares their magnitudes. The carbon cycle gives rise to two climate feedback terms: the concentration–carbon feedback, resulting from the uptake of carbon by land and ocean as a biogeochemical response to the atmospheric CO2 concentration, and the climate–carbon feedback, resulting from the effect of climate change on carbon fluxes. In the earth system models of the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP), climate–carbon feedback on warming is positive and of a similar size to the cloud feedback. The concentration–carbon feedback is negative; it has generally received less attention in the literature, but in magnitude it is 4 times larger than the climate–carbon feedback and more uncertain. The concentration–carbon feedback is the dominant uncertainty in the allowable CO2 emissions that are consistent with a given CO2 concentration scenario. In modeling the climate response to a scenario of CO2 emissions, the net carbon cycle feedback is of comparable size and uncertainty to the noncarbon–climate response. To quantify simulated carbon cycle feedbacks satisfactorily, a radiatively coupled experiment is needed, in addition to the fully coupled and biogeochemically coupled experiments, which are referred to as coupled and uncoupled in C4MIP. The concentration–carbon and climate–carbon feedbacks do not combine linearly, and the concentration–carbon feedback is dependent on scenario and time. [ABSTRACT FROM AUTHOR]

A new moist turbulence parameterization is presented and implemented in the Community Atmosphere Model (CAM). It is derived from Grenier and Bretherton but has been heavily modified to improve its numerical stability and efficiency with the long time steps used in climate models. A goal was to provide a more physically realistic treatment of marine stratocumulus-topped boundary layers than in the current CAM. Key features of the scheme include use of moist-conserved variables, an explicit entrainment closure for convective layers, diagnosis of turbulent kinetic energy (TKE) for computation of turbulent diffusivities, an efficient new formulation of TKE transport as a relaxation to layer-mean TKE, and unified treatment of all turbulent layers in each atmospheric column. The scheme is compared with the default turbulence parameterizations in the CAM using three single-column modeling cases, using both operational and high vertical and time resolution. Both schemes performed comparably well on the dry convective boundary layer case. For a stable boundary layer case, the default CAM overdeepens the boundary layer unless its free-tropospheric mixing length is greatly reduced, whereupon the new scheme and default CAM again both perform well at both tested resolutions. A nocturnal stratocumulus case was much better simulated by the new scheme than the default CAM, with much less resolution sensitivity. Global climate simulations with the new scheme in tandem with a new shallow cumulus parameterization are presented in a companion paper. [ABSTRACT FROM AUTHOR]

Climate model simulations consistently show that surface temperature over land increases more rapidly than over sea in response to greenhouse gas forcing. The enhanced warming over land is not simply a transient effect caused by the land–sea contrast in heat capacities, since it is also present in equilibrium conditions. This paper elucidates the transient adjustment processes over time scales of days to weeks of the surface and tropospheric climate in response to a doubling of CO2 and to changes in sea surface temperature (SST), imposed separately and together, using ensembles of experiments with an atmospheric general circulation model. These adjustment processes can be grouped into three stages: immediate response of the troposphere and surface processes (day 1), fast adjustment of surface processes (days 2–5), and adjustment of the whole troposphere (days 6–20). Some land surface warming in response to doubled CO2 (with unchanged SSTs) occurs immediately because of increased downward longwave radiation. Increased CO2 also leads to reduced plant stomatal resistance and hence restricted evaporation, which increases land surface warming in the first day. Rapid reductions in cloud amount lead in the next few days to increased downward shortwave radiation and further warming, which spreads upward from the surface, and by day 5 the surface and tropospheric response is statistically consistent with the equilibrium value. Land surface warming in response to imposed SST change (with unchanged CO2) is slower. Tropospheric warming is advected inland from the sea, and over land it occurs at all levels together rather than spreading upward from the surface. The atmospheric response to prescribed SST change in about 20 days is statistically consistent with the equilibrium value, and the warming is largest in the upper troposphere over both land and sea. The land surface warming involves reduction of cloud cover and increased downward shortwave radiation, as in the experiment with CO2 change, but in this case it is due to the restriction of moisture supply to the land (indicated by reduced soil moisture), whereas in the CO2 forcing experiment it is due to restricted evaporation despite increased moisture supply (indicated by increased soil moisture). The warming over land in response to SST change is greater than over the sea and is the dominant contribution to the land–sea warming contrast under enhanced CO2 forcing. [ABSTRACT FROM AUTHOR]

In this paper, an idealized framework based on a cloud-topped mixed layer model is developed for investigating feedbacks between subtropical stratocumulus (Sc) and global warming. The two principal control parameters are Sc-region sea surface temperature (SST) and intertropical convergence zone (ITCZ) SST (which controls the temperature and mean subsidence profiles above the Sc). The direct effect of CO2 doubling (leaving all other parameters fixed) is tested and found to somewhat reduce liquid water path; discussion of this effect on the SST-change simulations is included. The presence of a cold boundary layer is found to significantly affect the temperature and subsidence rate just above cloud top by enhancing lower-tropospheric diabatic cooling in this region. A simple representation of this effect (easily generalizable to a more realistic boundary layer model) is developed. Steady-state solutions are analyzed as a function of local and ITCZ SST. Two climate change scenarios are considered. The first scenario is an equal increase of local and ITCZ SSTs. In this case, predicted boundary layer depth and cloud thickness increase. This is found in a simplified context to result from subsidence and entrainment decreases due to increased static stability in a warmer climate. In the second case, local SST change is diagnosed from a surface energy balance under the assumption that ocean heat transport remains unchanged. In this case, predicted boundary layer depth decreases. Cloud continues to thicken with rising ITCZ SST, but at a rate much reduced in comparison to the equal-warming scenario. This cloud shading feedback keeps SST in the Sc region nearly constant as the ITCZ SST increases. Model sensitivity to aerosol indirect effects is also considered by varying the assumed droplet concentration. The resulting change in liquid water path is small, suggesting a weaker dependence on second indirect effect than found in previous studies. [ABSTRACT FROM AUTHOR]

The article focuses on the myth about the agreement among climate scientists in the 1970s, on the global cooling or the return of ice age in due time. Climate researcher Reid Bryson is the one who integrated the description of the climate change and the consequence of global warming. Due to this myth, scientific literature on greenhouse warming grew, as well as research enterprises arose. Discourses tackling about the potential problems of environmental pollution including the polluting effects of urban air pollution, pesticides, aerosols and carbon dioxide, dominated among media coverage, government, and researchers. An overview of the global temperature records and literatures is offered. Meanwhile, the review of the climate science literature from 1965 to 1979 was proven to be a faux.

In this paper the extensive integrations produced for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) are used to examine the relationship between ENSO and monsoons at interannual and decadal time scales. The study begins with an analysis of the monsoon simulation in the twentieth-century integrations. Six of the 18 models were found to have a reasonably realistic representation of monsoon precipitation climatology. For each of these six models SST and anomalous precipitation evolution along the equatorial Pacific during El Niño events display considerable differences when compared to observations. Out of these six models only four [Geophysical Fluid Dynamics Laboratory Climate Model versions 2.0 and 2.1 (GFDL_CM_2.0 and GFDL_CM_2.1), Meteorological Research Institute (MRI) model, and Max Planck Institute ECHAM5 (MPI_ECHAM5)] exhibit a robust ENSO–monsoon contemporaneous teleconnection, including the known inverse relationship between ENSO and rainfall variations over India. Lagged correlations between the all-India rainfall (AIR) index and Niño-3.4 SST reveal that three models represent the timing of the teleconnection, including the spring predictability barrier, which is manifested as the transition from positive to negative correlations prior to the monsoon onset. Furthermore, only one of these three models (GFDL_CM_2.1) captures the observed phase lag with the strongest anticorrelation of SST peaking 2–3 months after the summer monsoon, which is partially attributable to the intensity of the simulated El Niño itself. The authors find that the models that best capture the ENSO–monsoon teleconnection are those that correctly simulate the timing and location of SST and diabatic heating anomalies in the equatorial Pacific and the associated changes to the equatorial Walker circulation during El Niño events. The strength of the AIR-Niño-3.4 SST correlation in the model runs waxes and wanes to some degree on decadal time scales. The overall magnitude and time scale for this decadal modulation in most of the models is similar to that seen in observations. However, there is little consistency in the phase among the realizations, suggesting a lack of predictability of the decadal modulation of the monsoon–ENSO relationship. The analysis was repeated for each of the four models using results from integrations in which the atmospheric CO2 concentration was raised to twice preindustrial values. From these “best” models in the double CO2 simulations there are increases in both the mean monsoon rainfall over the Indian subcontinent (by 5%–25%) and in its interannual variability (5%–10%). For each model the ENSO–monsoon correlation in the global warming runs is very similar to that in the twentieth-century runs, suggesting that the ENSO–monsoon connection will not weaken as global climate warms. This result, though plausible, needs to be taken with some caution because of the diversity in the simulation of ENSO variability in the coupled models that have been analyzed. Implications of the present results for monsoon prediction are discussed. [ABSTRACT FROM AUTHOR]

This paper presents an update on the detection and attribution of global annual mean surface air temperature changes, using recently developed climate models. In particular, it applies a new methodology that permits the inclusion of many more general circulation models (GCMs) into the analysis, and it also includes more recent observations. This methodology involves fitting a series of energy balance models (EBMs) to the GCM output in order to estimate the temporal response patterns to the various forcings. Despite considerable spread in estimated EBM parameters, characteristics of model performance, such as the transient climate response, appear to be more constrained for each of the forcings. The resulting estimated response patterns are provided as input to the standard fingerprinting method used in previous studies. The estimated GCM responses to changes in greenhouse gases are detected in the observed record for all of the GCMs, and are generally found to be consistent with the observed changes; the same is generally true for the responses to changes in stratospheric aerosols from volcanic eruptions. GCM responses to changes in tropospheric sulfate aerosols and solar irradiance also appear consistent with the observed record, although the uncertainty is larger. Greenhouse gas and solar irradiance changes are found to have contributed to a best guess of ∼0.8 and ∼0.3 K warming over the 1901–2005 period, respectively, while sulfate aerosols have contributed a ∼0.4 K cooling. This analysis provides an observationally constrained estimate of future warming, which is found to be fairly robust across GCMs. By 2100, a warming of between about 1.5 and 4.5 K can be expected according to the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B emissions scenario. These results indicate an emerging constraint for global mean surface temperature responses to external forcings across GCMs, which is corroborated in the observed record. This implies that observationally constrained estimates of past warming and predictions of future warming are indeed becoming robust. [ABSTRACT FROM AUTHOR]

Observations in subtropical regions show that stratiform low cloud cover is well correlated with the lower-troposphere stability (LTS), defined as the difference in potential temperature θ between the 700-hPa level and the surface. The LTS can be regarded as a measure of the strength of the inversion that caps the planetary boundary layer (PBL). A stronger inversion is more effective at trapping moisture within the marine boundary layer (MBL), permitting greater cloud cover. This paper presents a new formulation, called the estimated inversion strength (EIS), to estimate the strength of the PBL inversion given the temperatures at 700 hPa and at the surface. The EIS accounts for the general observation that the free-tropospheric temperature profile is often close to a moist adiabat and its lapse rate is strongly temperature dependent. Therefore, for a given LTS, the EIS is greater at colder temperatures. It is demonstrated that while the seasonal cycles of LTS and low cloud cover fraction (CF) are strongly correlated in many regions, no single relationship between LTS and CF can be found that encompasses the wide range of temperatures occurring in the Tropics, subtropics, and midlatitudes. However, a single linear relationship between CF and EIS explains 83% of the regional/seasonal variance in stratus cloud amount, suggesting that EIS is a more regime-independent predictor of stratus cloud amount than is LTS under a wide range of climatological conditions. The result has some potentially important implications for how low clouds might behave in a changed climate. In contrast to Miller’s thermostat hypothesis that a reduction in the lapse rate (Clausius–Clapeyron) will lead to increased LTS and increased tropical low cloud cover in a warmer climate, the results here suggest that low clouds may be much less sensitive to changes in the temperature profile if the vertical profile of tropospheric warming follows a moist adiabat. [ABSTRACT FROM AUTHOR]

This paper examines variations of the surface air temperature (SAT) over China and the globe in the twentieth century simulated by 19 coupled climate models driven by historical natural and anthropogenic forcings. Most models perform well in simulating both the global and the Northern Hemispheric mean SAT evolutions of the twentieth century. The inclusion of natural forcings improves the simulation, in particular for the first half of the century. The reproducibility of the SAT averaged over China is lower than that of the global and hemispheric averages, but it is still acceptable. The contribution of natural forcings to the SAT over China in the first half of the century is not as robust as that to the global and hemispheric averages. No model could successfully produce the reconstructed warming over China in the 1920s. The prescribed natural and anthropogenic forcings in the coupled climate models mainly produce the warming trends and the decadal- to interdecadal-scale SAT variations with poor performances at shorter time scales. The prominent warming trend in the last half of the century over China and its acceleration in recent decades are weakly simulated. There are discrepancies between the simulated and observed regional features of the SAT trend over China. Few models could produce the summertime cooling over the middle part of eastern China (27°–36°N), while two models acceptably produce the meridional gradients of the wintertime warming trends, with north China experiencing larger warming. Limitations of the current state-of-the-art coupled climate models in simulating spatial patterns of the twentieth-century SAT over China cast a shadow upon their capability toward projecting credible geographical distributions of future climate change through Intergovernmental Panel on Climate Change (IPCC) scenario simulations. [ABSTRACT FROM AUTHOR]

The relative importance of the processes responsible for the annual cycle in the upper-ocean heat content in the Peru Current, in the southeastern tropical Pacific, was diagnosed from an oceanic analysis dataset. It was found that the annual cycle of heat content is forced mainly by insolation. However, the ocean dynamical processes play an important role in producing different regional budget characteristics. In a band 500 km from the coast of Peru, the annual heat content changes in this region are relatively large and can be approximated as sea surface temperature (SST) changes in a fixed-depth mixed layer. The annual cycle of the albedo associated with low-level clouds enhances the annual cycle in insolation, which explains the relatively strong annual cycle of heat content. These clouds, to a large extent, act as a feedback to SST, but a small additional forcing, which is proposed to be cold air advection in this paper, is needed to explain the fact that the maximum cloudiness leads the lowest SST by around a month. Ocean dynamics is important closer to the coast, where upwelling acts partly as damping of the heat content changes and forces it to peak earlier than farther offshore. In a band farther to the southwest, locally wind-forced thermocline motions, which become shallower (deeper) in the warm (cool) season, partially cancel the effect of net surface heat fluxes, whose annual cycle is comparable to that in the region previously mentioned, producing a relatively small annual cycle of heat content. The local forcing appears to be associated with the annual meridional displacements of the South Pacific anticyclone. The annual cycle in SST is also relatively small, which is probably due to the changes in the temperature of the water entrained into the mixed layer associated with the thermocline motions, but also to a mixed layer deeper than that closer to the coast. [ABSTRACT FROM AUTHOR]

This paper reviews recent research on tropical cyclones and climate change from the perspective of event risk—the physical behavior of storms; vulnerability—the characteristics of a system that create the potential for impacts, but are independent of event risk; and also outcome risk—the integration of considerations of vulnerability with event risk to characterize an event that causes losses. The paper concludes that with no trend identified in various metrics of hurricane damage over the twentieth century, it is exceedingly unlikely that scientists will identify large changes in historical storm behavior that have significant societal implications, though scientists may identify discernible changes in storm behavior. Looking to the future, until scientists conclude a) that there will be changes to storms that are significantly larger than observed in the past, b) that such changes are correlated to measures of societal impact, and c) that the effects of such changes are significant in the context of inexorable growth in population and property at risk, then it is reasonable to conclude that the significance of any connection of human-caused climate change to hurricane impacts necessarily has been and will continue to be exceedingly small. [ABSTRACT FROM AUTHOR]

Home runs in baseball—fair balls hit out of the field of play—have risen since 1980, driving strategic shifts in gameplay. Myriad factors likely account for these trends, with some speculating that global warming has contributed via a reduction in ballpark air density. Here we use observations from 100,000 Major League Baseball games and 240,000 individual batted balls to show that higher temperatures substantially increase home runs. We isolate human-caused warming with climate models, finding that >500 home runs since 2010 are attributable to historical warming. Several hundred additional home runs per season are projected due to future warming. Adaptations such as building domes on stadiums or shifting day games to night games reduce temperature's effects on America's pastime. Our results highlight the myriad ways that a warmer planet will restructure our lives, livelihoods, and recreation, some quantifiable and easily adapted to, as shown here, many others, not. [ABSTRACT FROM AUTHOR]

The climate of High Mountain Asia (HMA) has changed in recent decades. While the temperature is consistently increasing at a higher rate than the global warming rate, precipitation changes are inconsistent, with substantial temporal and spatial variation. Climate warming will have enormous consequences for hydroclimatic extremes. For the higher altitudes of the HMA, which are a significant source of water for the large rivers in Asia, often trends are calculated using a limited number of in situ observations mainly observed in valleys. This study explores the changes in mean, extreme, and compound-extreme climate variables and their seasonality along the full altitudinal range in HMA using daily ERA5 reanalysis data (1979–2018). Our results show that winter warming and summer wetting dominate the interior part of HMA. The results indicate a coherent significant increasing trend in the occurrence of heatwaves across all regions in HMA. The number of days with heavy precipitation shows more significant trends in southern and eastern basins than in other areas of HMA. The dry period occurrence shows a distinct demarcation between lower- and higher-altitude regions and is increasing for most basins. Although precipitation and temperature show variable tendencies, their compound occurrence is coherent in the monsoon-dominated basins. These changes in indicators of climatic extremes may imply substantial increases in the future occurrence of hazards such as floods, landslides, and droughts, which in turn impact economic production and infrastructure. [ABSTRACT FROM AUTHOR]

The 2021 northwest Pacific marine heatwave was favored by the atmospheric and oceanic conditions; changes in the mean climate due to anthropogenic warming made the event 43 times more likely. [ABSTRACT FROM AUTHOR]

This article discusses climate change and hurricanes. Papers that appeared in the scholarly journals "Nature" and "Science" during the summer of 2005 raised the question of global warming being the cause of the record-breaking hurricane season of 2005. The article examines that argument, noting that many scientists believe that human-induced climate warming is indeed real. Also discussed is the increasing intensity of hurricanes since 1975, as well as the rise in seas surface temperatures and greenhouse gases in the atmosphere.

Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. Here the importance of microphysical processes for the negative optical depth feedback is assessed by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. It is found that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, a very robust positive relationship between monthly mean LWP and temperature in CMIP5 models and observations is shown to exist in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. The results indicate that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback. [ABSTRACT FROM AUTHOR]

The mechanisms of model-projected atmospheric moisture budget change across North America are examined in simulations conducted with 22 models from phase 5 of the Coupled Model Intercomparison Project. Modern-day model budgets are validated against the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis. In the winter half year transient eddies converge moisture across the continent while the mean flow wets the west from central California northward and dries the southwest. In the summer half year there is widespread mean flow moisture divergence across the west and convergence over the Great Plains that is offset by transient eddy divergence. In the winter half year the models project drying for the southwest and wetting to the north. Changes in the mean flow moisture convergence are largely responsible across the west but intensified transient eddy moisture convergence wets the northeast. In the summer half year widespread declines in precipitation minus evaporation ( P − E) are supported by mean flow moisture divergence across the west and transient eddy divergence in the Great Plains. The changes in mean flow convergence are related to increases in specific humidity but also depend on changes in the mean flow including increased low-level divergence in the U.S. Southwest and a zonally varying wave that wets the North American west and east coasts in winter and dries the U.S. Southwest. Increased transient eddy fluxes occur even as low-level eddy activity weakens and arise from strengthened humidity gradients. A full explanation of North American hydroclimate changes will require explanation of mean and transient circulation changes and the coupling between the moisture and circulation fields. [ABSTRACT FROM AUTHOR]

An optimal projection for improving the skill of dynamical model forecasts is proposed. The proposed method uses statistical optimization techniques to identify the most skillful or most predictable patterns, and then projects forecasts onto these patterns. Applying the method to seasonal mean 2-m temperature from the Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) multimodel hindcast dataset reveals that the method improves skill only in South America and Africa, suggesting that the benefit of optimal projection is limited to certain regions, but can be substantial. Further investigation reveals that the improvement in skill comes not from optimal projection itself, but from the EOF prefiltering that is done to reduce the dimension of the optimization space. Thus, much of the improvement attributable to optimal projection can be achieved by suitable EOF filtering. Interestingly, models are found to generate patterns that project only weakly on observational datasets but are strongly correlated between models. An important by-product of the method is a concise summary of the skillful or predictable structures in a given forecast. For the ENSEMBLES dataset, the method convincingly demonstrates that most of the seasonal prediction skill over continents comes from two components, ENSO and the global warming trend. In addition, the method can be used to determine whether a pattern exists that is well predicted by one model but not by another model (complementary skill). [ABSTRACT FROM AUTHOR]