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Much of our understanding of atmospheric circulation comes from relationships between aspects of the circulation and the mean state of the atmosphere. In particular, the concept of mean available potential energy (MAPE) has been used previously to relate the strength of the extratropical storm tracks to the zonal-mean temperature and humidity distributions. Here, we calculate for the first time the MAPE of the zonally varying (i.e., three-dimensional) time-mean state of the atmosphere including the effects of latent heating. We further calculate a local MAPE by restricting the domain to an assumed eddy size, and we partition this local MAPE into convective and nonconvective components. Local convective MAPE maximizes in the subtropics and midlatitudes, in many cases in regions of the world that are known to have intense convection. Local nonconvective MAPE has a spatial pattern similar to the Eady growth rate, although local nonconvective MAPE has the advantage that it takes into account latent heating. Furthermore, the maximum potential ascent associated with local nonconvective MAPE is related to the frequency of warm conveyor belts (WCBs), which are ascending airstreams in extratropical cyclones with large impacts on weather. This maximum potential ascent can be calculated based only on mean temperature and humidity, and WCBs tend to start in regions of high maximum potential ascent on a given day. These advances in the use of MAPE are expected to be helpful to connect changes in the mean state of the atmosphere, such as under global warming, to changes in important aspects of extratropical circulation.

The response of the Pacific Walker circulation (WC) to long-term warming remains uncertain. Here, we diagnose contributions to the WC response in comprehensive and idealized general circulation model (GCM) simulations. We find that the spread in WC response is substantial across both the Coupled Model Intercomparison Project (CMIP6) and the Atmospheric Model Intercomparison Project (AMIP) models, implicating differences in atmospheric models in the spread in projected WC strength. Using a moist static energy (MSE) budget, we evaluate the contributions to changes in the WC strength related to changes in gross moist stability (GMS), horizontal MSE advection, radiation, and surface fluxes. We find that the multimodel mean WC weakening is mostly related to changes in GMS and radiation. Furthermore, the spread in WC response is related to the spread in GMS and radiation responses. The GMS response is potentially sensitive to parameterized convective entrainment which can affect lapse rates and the depth of convection. We thus investigate the role of entrainment in setting the GMS response by varying the entrainment rate in an idealized GCM. The idealized GCM is run with a simplified Betts-Miller convection scheme, modified to represent entrainment. The weakening of the WC with warming in the idealized GCM is dampened when higher entrainment rates are used. However, the spread in GMS responses due to differing entrainment rates is much smaller than the spread in GMS responses across CMIP6 models. Therefore, further work is needed to understand the large spread in GMS responses across CMIP6 and AMIP models.

Subgrid processes in global climate models are represented by parameterizations which are a major source of uncertainties in simulations of climate. In recent years, it has been suggested that machine-learning (ML) parameterizations based on high-resolution model output data could be superior to traditional parameterizations. Currently, both traditional and ML parameterizations of subgrid processes in the atmosphere are based on a single-column approach, which only use information from single atmospheric columns. However, single-column parameterizations might not be ideal since certain atmospheric phenomena, such as organized convective systems, can cross multiple grid boxes and involve slantwise circulations that are not purely vertical. Here we train neural networks (NNs) using non-local inputs spanning over 3$\times$3 columns of inputs. We find that including the non-local inputs improves the offline prediction of a range of subgrid processes. The improvement is especially notable for subgrid momentum transport and for atmospheric conditions associated with mid-latitude fronts and convective instability. Using an interpretability method, we find that the NN improvements partly rely on using the horizontal wind divergence, and we further show that including the divergence or vertical velocity as a separate input substantially improves offline performance. However, non-local winds continue to be useful inputs for parameterizating subgrid momentum transport even when the vertical velocity is included as an input. Overall, our results imply that the use of non-local variables and the vertical velocity as inputs could improve the performance of ML parameterizations, and the use of these inputs should be tested in online simulations in future work., Comment: 38 pages, 21 figures (7 figures in the main file)

Much of our understanding of atmospheric circulation comes from relationships between aspects of the circulation and the mean state of the atmosphere. In particular, the concept of mean available potential energy (MAPE) has been used previously to relate the strength of the extratropical storm tracks to the zonal-mean temperature and humidity distributions. Here, we calculate for the first time the MAPE of the zonally varying (i.e., three-dimensional) time-mean state of the atmosphere including the effects of latent heating. We further calculate a local MAPE by restricting the domain to an assumed eddy size, and we partition this local MAPE into convective and nonconvective components. Local convective MAPE maximizes in the subtropics and midlatitudes, in many cases in regions of the world that are known to have intense convection. Local nonconvective MAPE has a spatial pattern similar to the Eady growth rate, although local nonconvective MAPE has the advantage that it takes into account latent heating. Furthermore, the maximum potential ascent associated with local nonconvective MAPE is related to the frequency of warm conveyor belts (WCBs), which are ascending airstreams in extratropical cyclones with large impacts on weather. This maximum potential ascent can be calculated based only on mean temperature and humidity, and WCBs tend to start in regions of high maximum potential ascent on a given day. These advances in the use of MAPE are expected to be helpful to connect changes in the mean state of the atmosphere, such as under global warming, to changes in important aspects of extratropical circulation.

Future climate simulations indicate that the Mediterranean Basin will experience large low-level circulation changes during winter, characterized by a strong anomalous ridge that drives a regional precipitation decline. Previous research highlighted how shifts in stationary wave structure and the atmospheric response to reduced warming of the Mediterranean Sea relative to land could explain the development of this anomalous pressure high. Here, we expand on these results and provide new arguments for why and how the Mediterranean is projected to experience large circulation changes during winter. First, we find that zonal asymmetries in the vertical structure of stationary waves are important to explain the enhanced circulation response in the region and that these asymmetries are related through the external mode to the vertical structure of the mean zonal wind. Second, in winter, the Mediterranean is located just to the north of the Hadley cell edge and consequently is relatively free of large-scale descent; together with low near-surface static stability above the sea, this condition allows the weaker warming trend above the sea to propagate to the low troposphere and trigger a major circulation response. During summer, however, remotely forced descent and strong static stability prevent the cooling anomaly from expanding upward. Most of the intermodel scatter in the projected low-level circulation response in winter is related to the spread in upper-tropospheric dynamical trends. Importantly, because climate models exhibit too much vertical coherence over the Mediterranean, they likely overestimate the sensitivity of Mediterranean near-surface circulation to large-scale dynamical changes.

Several physical mechanisms have been proposed for projected changes in mean precipitation in the tropics under climate warming. In particular, the “wet-get-wetter” mechanism describes an amplification of the pattern of precipitation in a moister atmosphere, and the “warmer-get-wetter” mechanism describes enhanced upward motion and precipitation in regions where the increase in SST exceeds the tropical-mean increase. Studies of the current climate have shown that surface convergence over the tropical oceans is largely driven by horizontal gradients of low-level temperature, but the influence of these gradients on the precipitation response under climate warming has received little attention. Here, a simple model is applied to give a decomposition of changes in precipitation over tropical oceans in twenty-first-century climate model projections. The wet-get-wetter mechanism and changes in surface convergence are found to be of widespread importance, whereas the warmer-get-wetter mechanism is primarily limited to negative anomalies in the tropical southern Pacific. Furthermore, surface convergence is linked to gradients of boundary layer temperature using an atmospheric mixed layer model. Changes in surface convergence are found to be strongly related to changes in the Laplacian of boundary layer virtual temperature, and, to a lesser extent, the Laplacian of SST. Taken together, these results suggest that a “Laplacian-of-warming” mechanism is of comparable importance to wet get wetter and warmer get wetter for the response of precipitation to climate change over tropical oceans.

Climate models predict a distinct seasonality to future changes in daily extreme precipitation. In particular, models project that over land in the extratropical Northern Hemisphere the summer resp...

The circulation of the Northern Hemisphere extratropical troposphere has changed over recent decades, with marked decreases in extratropical cyclone activity and eddy kinetic energy (EKE) in summer and increases in the fraction of precipitation that is convective in all seasons. Decreasing EKE in summer is partly explained by a weakening meridional temperature gradient, but changes in vertical temperature gradients and increasing moisture also affect the mean available potential energy (MAPE), which is the energetic reservoir from which extratropical cyclones draw. Furthermore, the relation of changes in mean thermal structure and moisture to changes in convection associated with extratropical cyclones is poorly understood. Here we calculate trends in MAPE for the Northern extratropics in summer over the years 1979-2017, and we decompose MAPE into both convective and nonconvective components. Nonconvective MAPE decreased over this period, consistent with decreases in EKE and extratropical cyclone activity, but convective MAPE increased, implying an increase in the energy available to convection. Calculations with idealized atmospheres indicate that nonconvective and convective MAPE both increase with increasing mean surface temperature and decrease with decreasing meridional surface temperature gradient, but convective MAPE is relatively more sensitive to the increase in mean surface temperature. These results connect changes in the atmospheric mean state with changes in both large-scale and convective circulations, and they suggest that extratropical cyclones can weaken even as their associated convection becomes more energetic.

Attempts to use machine learning to develop atmospheric parameterizations have mainly focused on subgrid effects on temperature and moisture, but subgrid momentum transport is also important in sim...

A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows and potential for these to worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project of the GEWEX (Global Energy and Water Exchanges) Hydroclimatology Panel. Here, we summarize the main findings so far and suggest future directions for research, including: the benefits of convection-permitting climate modelling; towards understanding mechanisms of change; the usefulness of temperature-scaling relations; towards detecting and attributing extreme rainfall change; and the need for international coordination and collaboration. Evidence suggests that the intensity of long-duration (1 day+) heavy precipitation increases with climate warming close to the Clausius–Clapeyron (CC) rate (6–7% K −1 ), although large-scale circulation changes affect this response regionally. However, rare events can scale at higher rates, and localized heavy short-duration (hourly and sub-hourly) intensities can respond more strongly (e.g. 2 × CC instead of CC). Day-to-day scaling of short-duration intensities supports a higher scaling, with mechanisms proposed for this related to local-scale dynamics of convective storms, but its relevance to climate change is not clear. Uncertainty in changes to precipitation extremes remains and is influenced by many factors, including large-scale circulation, convective storm dynamics andstratification. Despite this, recent research has increased confidence in both the detectability and understanding of changes in various aspects of intense short-duration rainfall. To make further progress, the international coordination of datasets, model experiments and evaluations will be required, with consistent and standardized comparison methods and metrics, and recommendations are made for these frameworks. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

Tropical precipitation clusters exhibit power-law frequency distributions in area and volume (integrated precipitation), implying a lack of characteristic scale in tropical convective organization. However, it remains unknown what gives rise to the power laws and how the power-law exponents for area and volume are related to one another. Here, we explore the perspective that precipitation clusters are islands above a convective threshold on a rough column-water-vapor (CWV) topography. This perspective is supported by the agreement between the precipitation clusters and CWV islands in their frequency distributions as well as fractal dimensions. Power laws exist for CWV islands at different thresholds through the CWV topography, suggesting that the existence of power-laws is not specifically related to local precipitation dynamics, but is rather a general feature of CWV islands. Furthermore, the frequency distributions and fractal dimensions of the clusters can be reproduced when the CWV field is modeled to be self-affine with a roughness exponent of 0.3. Self-affine scaling theory relates the statistics of precipitation clusters to the roughness exponent; it also relates the power-law slopes for area and volume without involving the roughness exponent. Thus, the perspective of precipitation clusters as CWV islands provides a useful framework to consider many statistical properties of the precipitation clusters, particularly given that CWV is well-observed over a wide range of length scales in the tropics. However, the statistics of CWV islands at the convective threshold imply a smaller roughness than is inferred from the power spectrum of the bulk CWV field, and further work is needed to understand the scaling of the CWV field., Comment: 22 pages, 9 figures

A promising approach to improve climate-model simulations is to replace traditional subgrid parameterizations based on simplified physical models by machine learning algorithms that are data-driven. However, neural networks (NNs) often lead to instabilities and climate drift when coupled to an atmospheric model. Here we learn an NN parameterization from a high-resolution atmospheric simulation in an idealized domain by coarse graining the model equations and output. The NN parameterization has a structure that ensures physical constraints are respected, and it leads to stable simulations that replicate the climate of the high-resolution simulation with similar accuracy to a successful random-forest parameterization while needing far less memory. We find that the simulations are stable for a variety of NN architectures and horizontal resolutions, and that an NN with substantially reduced numerical precision could decrease computational costs without affecting the quality of simulations., 23 pages, 6 figures (2 figures in main file)

Solar geoengineering that aims to offset global warming could nonetheless alter atmospheric temperature gradients and humidity and thus affect the extratropical storm tracks. Here, we first analyze climate model simulations from experiment G1 of the Geoengineering Model Intercomparison Project, in which a reduction in incoming solar radiation balances a quadrupling of CO2. The Northern Hemisphere extratropical storm track weakens by a comparable amount in G1 as it does for increased CO2 only. The Southern Hemisphere storm track also weakens in G1, in contrast to a strengthening and poleward shift for increased CO2. Using mean available potential energy, we show that the changes in zonal‐mean temperature and humidity are sufficient to explain the different responses of storm‐track intensity. We also demonstrate similar weakening in a more complex geoengineering scenario. Our results offer insight into how geoengineering affects storm tracks, highlighting the potential for geoengineering to induce novel climate changes.

Changes in extreme precipitation are amongst the most impactful consequences of global warming, with potential effects ranging from increased flood risk and landslides to crop failures and impacts on ecosystems. Thus, understanding historical and future changes in extreme precipitation is not only important from a scientific perspective, but also has direct societal relevance.However, while most current research has focused on annual precipitation extremes and their response to warming, it has recently been noted that climate model projections show a distinct seasonality to future changes in extreme precipitation. In particular, CMIP5 models suggest that over Northern Hemisphere (NH) land the summer response is weaker than the winter response in terms of percentage changes.Here we investigate changes in seasonal precipitation extremes using observations and simulations with coupled climate models. First, we analyse observed trends from the Hadley Centre’s global climate extremes dataset (HadEX2) to investigate to what extent there is already a difference between summer and winter trends over NH land. Second, we use 40 ensemble members from the CESM Large Ensemble to characterize the role played by internal variability in trends over the historical period. Lastly, we use CMIP5 simulations to explore the possibility of a link between the seasonality of changes in precipitation extremes and decreases in surface relative humidity over land.

Regional projections of daily extreme precipitation are uncertain, but can be decomposed into thermodynamic and dynamic contributions to improve understanding. While thermodynamics alone uniformly increase extreme precipitation, dynamical processes introduce regional variations.

Projections of precipitation extremes in simulations with global climate models are very uncertain in the tropics, in part because of the use of parameterizations of deep convection and model deficiencies in simulating convective organization. Here, we analyse precipitation extremes in high-resolution simulations that are run without a convective parameterization on a quasi-global aquaplanet. The frequency distributions of precipitation rates and precipitation cluster sizes in the tropics of a control simulation are similar to the observed distributions. In response to climate warming, 3 h precipitation extremes increase at rates of up to 9 % K − 1 in the tropics because of a combination of positive thermodynamic and dynamic contributions. The dynamic contribution at different latitudes is connected to the vertical structure of warming using a moist static stability. When the precipitation rates are first averaged to a daily timescale and coarse-grained to a typical global climate-model resolution prior to calculating the precipitation extremes, the response of the precipitation extremes to warming becomes more similar to what was found previously in coarse-resolution aquaplanet studies. However, the simulations studied here do not exhibit the high rates of increase of tropical precipitation extremes found in projections with some global climate models. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

The Eliassen–Palm (EP) flux is an important diagnostic for wave propagation and wave–mean flow interaction in the atmosphere. Here, two moist formulations of the EP flux are compared with the traditional dry EP flux, and their links to the surface westerlies are analyzed using reanalysis data and simulations with GCMs. The first moist formulation of the EP flux modifies only the static stability to account for latent heat release by eddies, while the second moist formulation simply replaces all potential temperatures with equivalent potential temperatures. For reanalysis data, the peak upward EP flux in the lower troposphere is farther equatorward and stronger when the moist formulations are used, with greater changes for the second moist formulation. The moist formulations have the advantage of giving a closer relationship over the seasonal cycle between the latitudes of the peak surface westerlies and the peak upward EP flux. In simulations with a comprehensive GCM, the dry and moist upward EP fluxes shift poleward by a similar amount as the climate warms. In simulations over a wider range of climates with an idealized GCM, the surface westerlies can shift both poleward and equatorward with warming, and they are influenced by an anomalous region of dry EP flux divergence near the subtropical jet. Using moist EP fluxes weakens this anomalous divergence in the idealized GCM simulations, and the shifts in the surface westerlies can then be understood through changes in the preference for equatorward or poleward wave propagation.

The entropy budget of the atmosphere is examined in simulations of radiative-convective equilibrium with a cloud-system resolving model over a wide range of surface temperatures from 281 to 311 K. Irreversible phase changes and the diffusion of water vapor account for more than half of the irreversible entropy production within the atmosphere, even in the coldest simulation. As the surface temperature is increased, the atmospheric radiative cooling rate increases, driving a greater entropy sink that must be matched by greater irreversible entropy production. The entropy production resulting from irreversible moist processes increases at a similar fractional rate as the entropy sink and at a lower rate than that implied by Clausius-Clapeyron scaling. This allows the entropy production from frictional drag on hydrometeors and on the atmospheric flow to also increase with warming, in contrast to recent results for simulations with global climate models in which the work output decreases with warming. A set of approximate scaling relations is introduced for the terms in the entropy budget as the surface temperature is varied, and many of the terms are found to scale with the mean surface precipitation rate. The entropy budget provides some insight into changes in frictional dissipation in response to warming or changes in model resolution, but it is argued that frictional dissipation is not closely linked to other measures of convective vigor.

Extreme precipitation over land has increased over the wettest and driest regions and is likely to keep intensifying over the twenty-first century. This has key implications for dry regions, which may be unprepared for the potential related flooding.

Cyclones are a key element of extratropical weather and frequently lead to extreme events like wind storms and heavy precipitation. Understanding potential changes of cyclone frequency and intensity is thus essential for a proper assessment of climate change impacts. Here the behavior of extratropical cyclones under strongly varying climate conditions is investigated using idealized climate model simulations in an aquaplanet setup. A cyclone tracking algorithm is applied to assess various statistics of cyclone properties such as intensity, size, lifetime, displacement velocity, and deepening rates. In addition, a composite analysis of intense cyclones is performed. In general, the structure of extratropical cyclones in the idealized simulations is very robust, and changes in major cyclone characteristics are relatively small. Median cyclone intensity, measured in terms of minimum sea level pressure and lower-tropospheric relative vorticity, has a maximum in simulations with global mean temperature slightly warmer than present-day Earth, broadly consistent with the behavior of the eddy kinetic energy analyzed in previous studies. Maximum deepening rates along cyclone tracks behave similarly and are in agreement with linear quasigeostrophic growth rates if the effect of latent heat release on the stratification is taken into account. In contrast to moderate cyclones, the relative vorticity of intense cyclones continues to increase with warming to substantially higher temperatures, and this is associated with enhanced lower-tropospheric potential vorticity anomalies likely caused by increased diabatic heating. Moist processes may, therefore, lead to the further strengthening of intense cyclones in warmer climates even if cyclones weaken on average.

International audience; Human activity is changing Earth's climate. Now that this has been acknowledged and accepted in international negotiations, climate research needs to define its next frontiers.

The distribution of vertical velocities in the extratropical troposphere is skewed such that upward motions are faster than downward motions. This skewness is important for the intensity distribution of precipitation and for the effective static stability experienced by moist eddies. We show here that the skewness of the vertical velocity increases in magnitude as the climate warms in simulations with an idealized general circulation model (GCM), except in very warm climates. That the skewness increases with warming is consistent with studies of moist baroclinic instability which suggest that the area of updraughts should contract as the stratification approaches moist neutrality in warm climates. However, the increase in skewness with warming is much weaker in the fully nonlinear simulations as compared to what is found for unstable modes of moist baroclinic instability in the same GCM. Nonlinear equilibration to a macroturbulent state leads to a reduction in skewness in warm climates. Therefore, while the unstable modes may be relevant for some cases of cyclogenesis, they overestimate the effect of warming on the skewness of the overall distribution of the vertical velocity. Remarkably, the most unstable mode transitions from a quasi‐periodic wave to an isolated diabatic Rossby vortex at sufficiently high temperatures, with possible implications for fast‐growing disturbances in warm climates. Keywords: skewness, vertical velocity, non‐Gaussian,moist baroclinic instability, diabatic Rossby vortex, diabatic Rossby wave, effective static stability, climate change, National Science Foundation (U.S.) (Grant AGS 1148594)

Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and moisture (surface specific humidity, column and up to 500-hPa precipitable water) are examined to construct analogue schemes for the winter [December–February (DJF)] of the “Pacific Coast California” (PCCA) region and the summer [June–August (JJA)] of the Midwestern United States (MWST). The detection diagnostics of analogue schemes are calibrated with 1979–2005 and validated with 2006–14 NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). All analogue schemes are found to significantly improve upon MERRA precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events in the MWST. When evaluated with the late twentieth-century climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), all analogue schemes produce model medians of heavy precipitation frequency that are more consistent with observations and have smaller intermodel discrepancies than model-based precipitation. Under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios, the CMIP5-based analogue schemes produce trends in heavy precipitation occurrence through the twenty-first century that are consistent with model-based precipitation, but with smaller intermodel disparity. The median trends in heavy precipitation frequency are positive for DJF over PCCA but are slightly negative for JJA over MWST. Overall, the analyses highlight the potential of the analogue as a powerful diagnostic tool for model deficiencies and its complementarity to an evaluation of heavy precipitation frequency based on model precipitation alone.

The moist available potential energy (MAPE) of a domain of air is defined as the maximum amount of kinetic energy that can be released through reversible adiabatic motions of its air parcels. The MAPE can be calculated using a parcel‐moving algorithm that finds the minimum enthalpy state for a given set of thermodynamic assumptions. However, the parcel‐moving algorithms proposed previously do not always find the minimum enthalpy state. In this article, we apply the Munkres algorithm to find the exact minimum enthalpy state and compare this exact algorithm with four inexact algorithms, including a new divide‐and‐conquer algorithm. The divide‐and‐conquer algorithm performs well in practice, while being simpler and faster than the Munkres algorithm, and it is recommended for future calculation of MAPE when the exact result is not required. Keywords: Poisson Equation, Laplacian growth, Diffusion Field, analytic solution, ramified network, Golden ratio

Climate models simulate a strong land-ocean contrast in the response of near-surface relative humidity to global warming: relative humidity tends to increase slightly over oceans but decrease substantially over land. Surface energy balance arguments have been used to understand the response over ocean but are difficult to apply over more complex land surfaces. Here, a conceptual box model is introduced, involving moisture transport between the land and ocean boundary layers and evapotranspiration, to investigate the decreases in land relative humidity as the climate warms. The box model is applied to idealized and full-complexity (CMIP5) general circulation model simulations, and it is found to capture many of the features of the simulated changes in land relative humidity. The box model suggests there is a strong link between fractional changes in specific humidity over land and ocean, and the greater warming over land than ocean then implies a decrease in land relative humidity. Evapotranspiration is of secondary importance for the increase in specific humidity over land, but it matters more for the decrease in relative humidity. Further analysis shows there is a strong feedback between changes in surface-air temperature and relative humidity, and this can amplify the influence on relative humidity of factors such as stomatal conductance and soil moisture., Submitted to Journal of Climate on May 1st, 2016

International audience; Extratropical cyclones are storm systems that are observed to travel preferentially within confined regions known as storm tracks. They contribute to precipitation, wind and temperature extremes in mid-latitudes. Cyclones tend to form where surface temperature gradients are large, and the jet stream influences their speed and direction of travel. Storm tracks shape the global climate through transport of energy and momentum. The intensity and location of storm tracks varies seasonally, and in response to other natural variations, such as changes in tropical sea surface temperature. A hierarchy of numerical models of the atmosphere-ocean system -- from highly idealized to comprehensive -- has been used to study and predict responses of storm tracks to anthropogenic climate change. The future position and intensity of storm tracks depend on processes that alter temperature gradients. However, different processes can have opposing influences on temperature gradients, which leads to a tug of war on storm track responses and makes future projections more difficult. For example, as climate warms, surface shortwave cloud radiative changes increase the Equator-to-pole temperature gradient, but at the same time, longwave cloud radiative changes reduce this gradient. Future progress depends on understanding and accurately quantifying the relative influence of such processes on the storm tracks.

Simulations with climate models show a land–ocean contrast in the response of P − E (precipitation minus evaporation or evapotranspiration) to global warming, with larger changes over ocean than over land. The changes over ocean broadly follow a simple thermodynamic scaling of the atmospheric moisture convergence: the so-called “wet-get-wetter, dry-get-drier” mechanism. Over land, however, the simple scaling fails to give any regions with decreases in P − E, and it overestimates increases in P − E compared to the simulations. Changes in circulation cause deviations from the simple scaling, but they are not sufficient to explain this systematic moist bias. It is shown here that horizontal gradients of changes in temperature and fractional changes in relative humidity, not accounted for in the simple scaling, are important over land and high-latitude oceans. An extended scaling that incorporates these gradients is shown to better capture the response of P − E over land, including a smaller increase in global-mean runoff and several regions with decreases in P − E. In the zonal mean over land, the gradient terms lead to a robust drying tendency at almost all latitudes. This drying tendency is shown to relate, in part, to the polar amplification of warming in the Northern Hemisphere, and to the amplified warming over continental interiors and on the eastern side of midlatitude continents.

Many climate studies assess trends and projections in heavy precipitation events using precipitation percentile (or quantile) indices. Here we investigate three different percentile indices that are commonly used. We demonstrate that these may produce very different results and thus require great care with interpretation. More specifically, consideration is given to two intensity-based indices and one frequency-based index, namely (a) all-day percentiles, (b) wet-day percentiles, and (c) frequency indices based on the exceedance of a percentile threshold. Wet-day percentiles are conditionally computed for the subset of wet events (with precipitation exceeding some threshold, e.g. 1 mm/d for daily precipitation). We present evidence that this commonly used methodology can lead to artifacts and misleading results if significant changes in the wet-day frequency are not accounted for. Percentile threshold indices measure the frequency of exceedance with respect to a percentile-based threshold. We show that these indices yield an assessment of changes in heavy precipitation events that is qualitatively consistent with all-day percentiles, but there are substantial differences in quantitative terms. We discuss the reasons for these effects, present a theoretical assessment, and provide a series of examples using global and regional climate models to quantify the effects in typical applications. Application to climate model output shows that these considerations are relevant to a wide range of typical climate-change applications. In particular, wet-day percentiles generally yield different results, and in most instances should not be used for the impact-oriented assessment of changes in heavy precipitation events., Climatic Change, 137 (1), ISSN:0165-0009, ISSN:1573-1480