General Circulation Model Research Articles

Projected changes in mean climate and extremes from downscaled high-resolution CMIP6 simulations in Australia

High-resolution climate change projections are required to understand local and regional climate change impacts. We used CCAM (Conformal Cubic Atmospheric Model) to dynamically downscale CMIP6 GCMs (Global Climate Models) over Australia under three emissions scenarios, producing a set of 60 simulations at a 10 km resolution. Previous work has evaluated the performance of the downscaled models in the historical period. Here, we evaluate the impact of end-of-century climate change in the downscaled CMIP6-CCAM models for mean and extreme climate under three Shared Socioeconomic Pathways (SSP126, 245 and 370). We find the changes in mean climate are similar in the host CMIP6 and downscaled models. For extreme temperature, we find that extreme maximum temperatures (TXx) increase by 3.4°C, while extreme minimum temperatures (TNn) warm by 3.0°C. Extreme precipitation generally increases in summer and decreases in winter; however, there is a large amount of inter-model variation in the location and magnitude of change. Consecutive dry days also decrease in most areas in Austral summer and increase in Austral winter. Heatwaves become more frequent and hotter by the end of the century. These results suggest a hotter, wetter Austral summer, with longer, more frequent and more intense heatwaves, and a hotter and drier Austral winter in most areas. This dataset provides useful new high-resolution information on how climate change is likely to impact Australia, which will be a valuable resource to underpin local adaptation responses to future impacts.

Emergency constraint-based CMIP6 predictions for future droughts on the Mongolian Plateau

Accurate predictions of future drought changes in the context of warming play an important role for both human social and ecological environments. This study aims to predict future droughts on the Mongolian Plateau using the latest Coupled Model Comparison Project dataset. First, the historical and future relationships of 17 Global Climate Models (GCMs) were constrained using the emergent constraints method to establish new predictions for future droughts under SSP2-4.5 and SSP5-8.5 scenarios. Based on two scenarios, spatial and temporal variations of future droughts on the Mongolian Plateau were analyzed. Future droughts will be worse compared to historical periods. In the SSP2-4.5 scenario, the future drought intensity shows an increasing trend, the frequency of drought gradually increases, and the spatial variation of both decreases gradually from the southwest to the northeast. Under the SSP5-8.5 scenario, the intensity and frequency of droughts increases from 2020 to 2060; from 2061 to 2100, the intensity and frequency of droughts show a decreasing trend. The spatial variation is uniform, with high values in the southwest and low values in the northeast.

The effect of Southern Ocean topography on the global MOC and abyssal water mass distribution

Abstract We investigate the role of Southern Ocean topography and wind stress in the deep and abyssal ocean overturning and water mass composition using a suite of idealized global ocean circulation models. Specifically, we address how the presence of a meridional ridge in the vicinity of Drake Passage and the formation of an associated Southern Ocean gyre influences the water mass composition of the abyssal cell. Our experiments are carried out using a numerical representation of the global ocean circulation in an idealized two-basin geometry under varying wind-stress and Drake Passage ridge height. In the presence of a low Drake Passage ridge the overall strength of the meridional overturning circulation is primarily influenced by wind stress, with a topographically-induced weakening of the mid-depth cell and concurrent strengthening of the abyssal cell occurring only after ridge height passes 2500m. Passive tracer experiments show that a strengthening mid-depth cell leads to increased abyssal ventilation by North Atlantic water masses, as more North Atlantic Deep Water (NADW) enters the Southern Ocean and then spreads into the Indo-Pacific. We repeat our tracer experiments without restoring in the high-latitude Southern Ocean in order to identify the origin of water masses that circulate through the Southern Ocean before sinking into the abyss as Antarctic Bottom Water. Our results from these “exchange” tracer experiments show that an increasing ridge height in Drake Passage and the concurrent gyre spin-up lead to substantially decreased NADW-origin waters in the abyssal ocean, as more surface waters from north of the ACC are transferred into the Antarctic Bottom Water formation region.

Should We Conserve Entropy or Energy when Computing CAPE with Mixed-Phase Precipitation Physics?

Abstract The rapidly increasing resolution of global atmospheric reanalysis and climate model datasets necessitates finding methods for computing convective available potential energy (CAPE) both efficiently and accurately. To this end, this article compares two common methods for computing CAPE which conserve either energy or entropy. Inaccuracies in these computations arise from both physical and numerical errors. For instance, computing CAPE with entropy conserved results in physical errors from nonequilibrium phase transitions but minimizes numerical errors because solutions are analytic at each height. In contrast, computing CAPE with energy conserved avoids these physical errors, but accumulates numerical errors that are grid-resolution-dependent because the numerical integration of a differential equation is required. Analysis of CAPE computed with large databases of soundings from the tropical Amazon and midlatitude storm environments shows that physical errors from the entropy method are typically 1%–3% as large as CAPE, which is comparable to the numerical errors from conserving energy with grid spacing of 25 and 250 m using explicit first-order and second-order integration schemes, respectively. Errors in entropy-based CAPE calculations are also insensitive to vertical grid spacing, in contrast to energy-based calculations whose error strongly scales with the grid spacing. It is shown that entropy-based methods are advantageous when intercomparing datasets with differing vertical resolution because they produce accurate and reasonably fast results that are insensitive to grid resolution, whereas a second-order energy-based method is advantageous when analyzing data with a consistent vertical resolution because of its superior computational efficiency. Significance Statement Convective available potential energy (CAPE) is a measure of instability in the atmosphere that helps forecasters and researchers understand when and where thunderstorms will form. The purpose of this article is to identify the most efficient and accurate methods for computing CAPE. Two methods are considered here, one that relates to the entropy (a measure of thermodynamic disorder) of an air parcel and one that relates to the energy of an air parcel. Results indicate that the entropy method is most accurate and insensitive to the resolution of the data used for the calculation (which can vary considerably), whereas the energy method uses the least computation time.

Improving Equatorial Upper Ocean Vertical Mixing in the NOAA/GFDL OM4 Model

AbstractDeficiencies in upper ocean vertical mixing parameterizations contribute to tropical upper ocean biases in global coupled general circulation models, affecting their simulated ocean heat uptake and ENSO variability. To better understand these deficiencies, we develop a suite of ocean model experiments including both idealized single column models and realistic global simulations. The vertical mixing parameterizations are first evaluated using large eddy simulations as a baseline to assess uncertainties and evaluate their implied turbulent mixing. Global models are then developed following NOAA/GFDL's 0.25° nominal horizontal grid spacing OM4 (uncoupled) configuration of the MOM6 ocean model, with various modifications that target biases in the original model. We test several enhancements to the existing mixing schemes and evaluate them against observational constraints from Tropical Atmosphere Ocean moorings and Argo floats. In particular, we find that we can improve the diurnal variability of mixing in OM4 via modifications to its surface boundary layer mixing scheme, and can improve the net mixing in the upper thermocline by reducing the background vertical viscosity, allowing for more realistic, less diffuse currents. The improved OM4 model better represents the mixing, leading to improved diurnal deep‐cycle variability, a more realistic time‐mean tropical thermocline structure, and a better Pacific Equatorial Undercurrent.

Vertical Velocity 3D Estimates from the Linear Vorticity Balance in the North Atlantic Ocean

Abstract Large-scale three-dimensional vertical movements of the world’s oceans play a fundamental role in their functioning, yet they are still overlooked. This study aims to enhance our understanding of the relationship between horizontal and vertical flows as a function of depth to derive some major characteristics of the w field from a relatively well-constrained variable. For this purpose, we analyze an eddy-permitting ocean general circulation model simulation, focusing on the linear vorticity balance (LVB) over the North Atlantic basin. For spatial scales greater than 5°, over more than 50-yr average, the LVB holds with less than 10% error over the whole depth range of most of the subtropical upper tachocline–upper ocean and part of the tropical one, away from western boundary currents and zonal tropical flows. The spatial extent of the balance diminishes in the intermediate ocean, particularly in the western half of the basin. Within the deep tachocline, the balance holds over large portions of the abyssal plains. Based on these results, the β-plane geostrophic vertical velocity is derived from the vertical indefinite integral of the geostrophic LVB from the surface. While its time mean aligns only qualitatively with the model reference w, it accurately captures the interannual variability over most of the basin, even close to eastern boundaries. However, it cannot reproduce the variability in the lower tropics, the western boundary, and the North Atlantic Current system. Our results emphasize the dominance of geostrophy in establishing most of the ocean model vertical flow variability.

Detectability Simulations of a Near-infrared Surface Biosignature on Proxima Centauri b with Future Space Observatories

Telescope missions are currently being designed that will make direct imaging of habitable exoplanets possible in the near future, and studies are needed to quantify the detectability of biosignature features in the planet’s reflectance spectrum. We simulated the detectability of a near-infrared-absorbing surface biosignature feature with simulated observations of the nearby exoplanet Proxima Centauri b. We modeled a biosignature spectral feature with a reflectance spectrum based on an anoxygenic photosynthetic bacterial species that has strong absorption at 1 μm, which could make it well suited for life on an M-dwarf-hosted planet. We modeled the distribution of this organism across the planet’s surface based on climate states from a 3D general circulation model (GCM) that were Archean- and Proterozoic-like exo-Earth analogs. We included the GCM states' prognostically simulated water clouds and added organic haze into the Archean-like atmospheres. We simulated observations of these Proxima Centauri b scenarios with the LUVOIR-A and B telescope concepts, with LUVOIR-B serving as a proxy to the planned Habitable Worlds Observatory. We calculated the integration times necessary to detect the biosignature and found that it would be detectable on Proxima Centauri b if the organism is moderately abundant (greater than a 1%–4% global surface area coverage), as long as the atmosphere is transmitting in the wavelength range under consideration. Small amounts of methane, clouds, and haze do not greatly impede detectability. We found preliminary evidence that such a biosignature would be detectable on exoplanets within 15 pc, but further investigations are needed to corroborate this.

A regional NEMO 4.0 configuration of the subpolar North Atlantic

The dynamics of the North Atlantic subpolar gyre (SPG) largely control the Atlantic Meridional Overturning Circulation (AMOC), thus affecting the long-term climate variability of the global ocean. Many key processes in the North Atlantic SPG, such as Gulf Stream detachment, eddy activity, deep convection and overflows, are frequently incorrectly presented or misrepresented in modern ocean general circulation models. Here, we present a new regional eddy-resolving model of the subpolar North Atlantic based on the NEMO4 configuration and analyze its ability to adequately represent the dynamics of the subpolar North Atlantic. The model performance is assessed using in situ data (cross-section hydrography, Argo and sea gliders), remote sensing data (satellite sea surface temperature and salinity) and the ANDRO and ARMOR3D products based on optimal interpolation products. In the next step, we analyze the effects of high-resolution forcing and several recent developments in ocean modeling to improve the model solution. The implementation of the self-diffusive momentum advection scheme with additional viscosity allows for the simulation of more realistic Deep Western Boundary Current and Irminger Rings lifecycle characteristics. The surface current feedback parameterization implemented in the forcing function and the modification of the kinetic energy budget in the upper ocean, especially in intensively eddying areas, simulate the behavior predicted by coupled models. While the model is sensitive to the implementation of cool skin–warm layer parameterization, this parameterization does not significantly improve the solution compared to the observational data. Regional implementation of the local-sigma vertical coordinate system in cascading areas allows overflow waters to spread over the ocean bottom more realistically. The remote effect of the implementation of the local-sigma coordinate is traced in the vertical thermohaline structure at the western slopes of the Irminger Sea and Iceland Basin as well as in the Deep Western Boundary Current in the Labrador Sea. Compared to z-partial step setting, local-sigma allows for correct representation of continuous densification of the water in the overturning part of the AMOC and thus North Atlantic Deep-Water formation. The potential of the new model configuration for analyzing the subpolar North Atlantic, including convective activity, is discussed.

An Implementation of the Particle Flow Filter in an Atmospheric Model

Abstract The particle flow filter (PFF) shows promise for fully nonlinear data assimilation (DA) in high-dimensional systems. However, its application in atmospheric models has been relatively unexplored. In this study, we develop a new algorithm, PFF-DART, in order to conduct DA for high-dimensional atmospheric models. PFF-DART combines the PFF and the two-step ensemble filtering algorithm in the Data Assimilation Research Testbed (DART), exploiting the highly parallel structure of DART. To evaluate the performance of PFF-DART, we conduct an observing system simulation experiment (OSSE) in a simplified atmospheric general circulation model and compare the performance of PFF-DART with an existing linear and Gaussian DA method. Using the PFF-DART algorithm, we demonstrate, for the first time, the capability of the PFF to yield stable results in a yearlong cycling DA OSSE. Moreover, PFF-DART retains the important ability of the PFF to improve the assimilation of nonlinear and non-Gaussian observations. Finally, we emphasize that PFF-DART is a versatile algorithm that can be integrated with numerous other non-Gaussian DA techniques. This quality makes it a promising method for further investigation within a more sophisticated numerical weather prediction model in the future. Significance Statement Data assimilation is an important tool in weather forecasting. However, fundamental issues arising from linear and Gaussian approximations still exist, which can limit our utilization of observations. The particle flow filter is a promising method that avoids these approximations, but efficient algorithms for this method have yet to be developed. In this study, we develop an algorithm for the particle flow filter that can be implemented in high-dimensional geophysical models. We have demonstrated, for the first time, that the particle flow filter runs efficiently for a yearlong experiment in an atmospheric model. The new algorithm also improves the results over a commonly used data assimilation method. The results in this work demonstrate the potential usage of the particle flow filter in the weather forecasting and other high-dimensional forecasting problems.

Climate change scenarios predict reduction in suitable habitats and range shifts for Ophiocordyceps sinensis (Berk.) in Hindu Kush Himalaya

The Hindu Kush Himalayan region has seen a faster pace of anthropogenic climate warming than the global average during the last 50 years. Since 1980s this region is experiencing intense climatic events notably elevation-dependent warming. Given its unique evolutionary background, rich variety of species, and significant endemism, it is crucial to comprehend the effects of climate change on species distributions in this area. Of particular interest are the fungi, which have been the subject of much fewer studies on how they will respond to climate change, despite the fact that they may have a significant role in the functioning and stability of ecosystems. We therefore selected Ophiocordyceps sinensis an alpine fungus species for predicting the effects of climate change on its distribution in Hindu Kush Himalaya. Regarded as one of the most expensive natural resources used in oriental medicine, Ophiocordyceps and its surrounding habitats are under threat from various ecological and anthropogenic factors. We used Species Distribution Modeling software Maxent 3.3.4 and a set of uncorrelated climatic (temperature and precipitation) and topographical (elevation, slope and aspect) variables at a spatial resolution of 2.5 arc minutes to model the suitable habitats. To predict the future distribution of O. sinensis we used future climate data from BCCCSM2- HR global circulation model for three emission scenarios of the shared socioeconomic pathways (SSPs) (SSP126, SSP245 and SSP585). Maxent model predicted current and future habitats with high accuracy. Current potential distribution map of O. sinensis shows that high suitability areas occur in India, China, Nepal and Bhutan. Prediction maps under all three scenarios showed a large reduction in suitable habitats as compared to current climatic conditions. Analysis of range change reveals that species exhibits both range expansion and range contraction under climate change scenarios. Range contraction is noticeably more than range expansion causing overall reduction in the suitable habitats occupied by O. sinensis. ‘Centroid Range Shift’ analysis revealed potential suitable habitats will shift to South-West direction under all future scenarios with almost overlapping centroids.

Assessment of rainwater resources in urban areas of reception basins of south-to-north water diversion project under climate change

The forecasting of future stormwater resources serves a pivotal role in gauging the potential effects of stormwater utilization on natural and societal systems. However, there has been limited research on the effect of climate change on future rainwater resources, particularly for large-scale water diversion projects. Based on global climate model data, future land use data and SCS-CN (soil conservation service curve number) model, this study proposed a calculation method of rainwater resources under different SSP scenarios in the future period, and carried out a case study on the cities in the receiving area of South-to-North Water Diversion Project (SNWDP). The results show that there will be an increase in the amount of rainfall in the future compared to 2020.The most significant increase in rainwater resources occurs in urban reception areas of the Eastern Route Project (ERP). However, according to future projections, the quantity of rainwater resources in the study area decreases from south to north. The spatial distribution of rainwater resources demonstrates a nearly normal distribution in the eastern and western routes and a bimodal distribution in the Central Route Project (CRP). In the context of global climate change, the increase in rainfall resources in the CRP may be beneficial for the establishment and implementation of the SNWDP. This study can provide a reference for analysing the uncertainty of rainwater resources in the future period under climate change. It can also provide guidance for the construction and develop scheduling schemes of the SNWDP, a world-class water diversion project.

Comparing Detected Trends and Projections of Rainfall Precipitation of Global Climate Models (CCM4) over Sultanate of Oman

Comparing Detected Trends and Projections of Rainfall Precipitation of Global Climate Models (CCM4) over Sultanate of Oman

Warm Jupiters around M dwarfs are great opportunities for extensive chemical, cloud, and haze characterisation with JWST

Context. The known population of short-period giant exoplanets around M-dwarf stars is slowly growing. These planets present an extraordinary opportunity for atmospheric characterisation and defy our current understanding of planetary formation. Furthermore, clouds and hazes are ubiquitous in warm exoplanets, but their behaviour is still poorly understood. Aims. We studied the case of a standard warm Jupiter around an M-dwarf star to show the opportunity of this exoplanet population for atmospheric characterisation. We aimed to derive the cloud, haze, and chemical budget of such planets using JWST. Methods. We leveraged a 3D global climate model, the generic PCM, to simulate the cloudy and cloud-free atmosphere of warm Jupiters around an M dwarf. We then post-processed our simulations to produce spectral phase curves and transit spectra as would be seen with JWST. Results. We show that, using the amplitude and offset of the spectral phase curves, we can directly infer the presence of clouds and hazes in the atmosphere of such giant planets. Chemical characterisation of multiple species is possible with an unprecedented signal- to-noise ratio, using the transit spectrum in one single visit. In such atmospheres, NH3 could be detected for the first time in a giant exoplanet. We make the case that these planets are key to understanding the cloud and haze budget in warm giants. Finally, such planets are targets of great interest for Ariel.

Future aridity and drought risk for traditional and super-intensive olive orchards in Portugal

Portugal, a leading olive oil producer, boasts six Protected Denomination of Origin (PDO) regions, with distinct olive orchard (OR) densities (traditional rainfed to super-intensive irrigated). This study aimed to assess future drought and aridity conditions and the impacts on ORs located in the PDOs. Therefore, drought and aridity indicators were considered for the historical (ERA5: 1981–2000) and future periods (2041–2060; 2081–2100), and anthropogenic forcing scenarios (RCP4.5 and RCP8.5), using a 7-member ensemble of global climate models. From Spearman’s correlation analysis, Annual Mean Aridity (AIA) was selected as the most representative indicator of the climate conditions, to which the ORs were exposed. Readily Available Soil Water (RAW; mm) was considered to represent the available soil water reservoir for olive trees. Moreover, the Olive Drought and Aridity Risk Index (ODAR) was developed to determine each OR's future risks. This index considered that the AIA and RAW were weighted by OR density fractions. In the future, southern Portugal will be more arid (0.69) than northern and central (0.60). ORs soil shows lower RAW in southern PDOs (< 60 mm) than in central and northern regions (> 90 mm). These results suggest that the south of ORs will be more exposed to water stress than the northern regions. According to ODAR, the ORs exposed to low and high risk will be mainly located in the central parts of the PDOs. In northern ORs, moderate to high risk will predominate. In the south, however, the risk will be very high, which means that the olive tree growth, fruit development, and olive oil quality could be negatively affected. Implementation of tailored adaptation measures will be required to improve the climate resiliency of the sector.

Customized Statistically Downscaled CMIP5 and CMIP6 Projections: Application in the Edwards Aquifer Region in South‐Central Texas

AbstractClimate projections are being used for decision‐making related to climate mitigation and adaptation and as inputs for impacts modeling related to climate change. The plethora of available projections presents end users with the challenge of how to select climate projections, known as the “practitioner's dilemma.” In addition, if an end‐user determines that existing projections cannot be used, then they face the additional challenge of producing climate projections for their region that are useful for their needs. We present a methodology with novel features to address the “practitioner's dilemma” for generating downscaled climate projections for specific applications. We use the Edwards Aquifer region (EAR) in south‐central Texas to demonstrate a process to select a subset of global climate models from both the CMIP5 and CMIP6 ensembles, followed by downscaling and verification of the accuracy of downscaled data against historical data. The results show that average precipitation changes range from a decrease of 10.4 mm to an increase of 25.6 mm, average temperature increases from 2.0°C to 4.3°C, and the number of days exceeding 37.8°C (100°F) increase by 35–70 days annually by the end of century. The findings enhance our understanding of the potential impacts of climate change on the EAR, essential for developing effective regional management strategies. Additionally, the results provide valuable scenario‐based projected data to be used for groundwater and spring flow modeling and present a clearly documented example addressing the “practitioner's dilemma” in the EAR.

Why Does Atmospheric Radiative Heating Weaken Midlatitude Cyclones?

AbstractRecent work has indicated that atmospheric radiative heating reduces the kinetic energy of large‐scale eddies in the midlatitudes. However, a physical mechanism that connects radiation to the midlatitude eddy kinetic energy is still uncertain. Using a high‐resolution general circulation model we perform an experiment in which the radiative cooling profile at each model time step is overwritten with the climatological mean, computed from a control simulation. This approach separates the mean and transient effects of radiative heating on the extratropical circulation. We find that, when radiative heating is fixed, the globally‐averaged eddy kinetic energy is enhanced by ∼6%. We show that thermal radiation dampens temperature anomalies near the surface and tropopause in low‐pressure systems, destroying eddy available potential energy and eddy kinetic energy. We identify this as a possible mechanism by which atmospheric radiative heating weakens midlatitude cyclones.

Assessment of Maximum Temperature for Future Time Series over Aurangabad, Maharashtra State, India

Climatic downscaling is an important tool used by many researchers in the field of climate to downscale climatic data available for global area to study the impacts of climate on smaller area. In climatic downscaling, there are mainly two types: 1) Statistical Downscaling and 2) Dynamical Downscaling. In the present study, statistical downscaling has been performed using SDSM (Statistical Downscaling Model) to find out future values of maximum temperatures (Tmax) over Aurangabad region (Latitude: 19.8911° N, Longitude: 75.1545° E). For this downscaling, CanESM2 (Canadian Earth System Model) CMIP5 (Coupled Model Intercomparison Project Phase 5) GCM (General Circulation Model) were selected and downscaling was performed under three different RCPs (Representative Concentration Pathways): RCP 2.6, RCP 4.5 and RCP 8.5. Downscaling model is calibrated and validated successfully over the baseline period 1961-2005 and results are presented graphically as well as statistically. Future downscaling values of maximum temperatures are presented with the help of three future time series: 2020s (2011-2040), 2050s (2041-2070) and 2080s (2071-2099) and it is observed that there is increase in the values of Tmax for the future time series with respect to the baseline period. Further the heat maps are developed for increasing monthly mean daily Tmax values under three RCPs with respect to the baseline period over the duration 2006 to 2013 and compared with increased observed monthly mean daily Tmax values over the same duration. This comparison has been done to assess the pattern of increasing monthly mean daily Tmax of downscaling results over Aurangabad region. All three RCPs are showing increasing values of monthly mean daily Tmax values for the selected three future time series with respect to the baseline period. Decade wise study of downscaling results is also showing increasing values of mean monthly daily Tmax with respect to the baseline period. Tmax values are predicted to be increased under RCP 2.6 by 1.10 0C, under RCP 4.5 by 2.13 0C and under RCP 8.5 by 4.20 0C at the end of 2099 which follows the prediction given by IPCC for global level temperature rise up to 2100.

A simple model linking radiative–convective instability, convective aggregation and large-scale dynamics

Abstract. A simple model is presented which is designed to analyse the relation between the phenomenon of convective aggregation at small scales and larger-scale variability that results from coupling between dynamics and moisture in the tropical atmosphere. The model is based on single-layer dynamical equations coupled to a moisture equation to represent the dynamical effects of latent heating and radiative heating. The moisture variable q evolves through the effect of horizontal convergence, nonlinear horizontal advection and diffusion. Following previous work, the coupling between moisture and dynamics is included in such a way that a horizontally homogeneous state may be unstable to inhomogeneous disturbances, and, as a result, localised regions evolve towards either dry or moist states, with divergence or convergence respectively in the horizontal flow. The time evolution of the spatial structure of the dry and moist regions is investigated using a combination of theory and numerical simulation. One aspect of the evolution is a spatial coarsening that, if moist regions and dry regions are interpreted as convecting and non-convecting respectively, represents a form of convective aggregation. When the weak temperature gradient (WTG) approximation (i.e. a local balance between heating and convergence) applies, and horizontal advection is neglected, the system reduces to a nonlinear reaction–diffusion equation for q, and the coarsening is a well-known aspect of such systems. When nonlinear advection of moisture is included, the large-scale flow that arises from the spatial pattern of divergence and convergence leads to a distinctly different coarsening process. When thermal and frictional damping and f-plane rotation are included in the dynamics, there is a dynamical length scale Ldyn that sets an upper limit for the spatial coarsening of the moist and dry regions. The f-plane results provide a basis for interpreting the behaviour of the system on an equatorial β plane, where the dynamics implies a displacement in the zonal direction of the divergence relative to q and hence to coherent equatorially confined zonally propagating disturbances, comprising separate moist and dry regions. In many cases the propagation speed and direction depend on the equatorial wave response to the moist heating, with the relative strength of the Rossby wave response to the Kelvin wave response determining whether the propagation is eastward or westward. Within this model, the key overall properties of the propagating disturbances, the spatial scale and the phase speed, depend on nonlinearity in the coupling between moisture and dynamics, and any linear theory for such disturbances therefore has limited usefulness. The model described here, in which the moisture and dynamical fields vary in two spatial dimensions and important aspects of nonlinearity are captured, provides an intermediate model between theoretical models based on linearisation and one spatial dimension and general circulation models (GCMs) or convection-resolving models.

Clarifying the impacts of climatic coupling on plastic-mulching potato production in the loess plateau of China

ContextThe ongoing changes in climate constitute a major risk factor for global potato production. Recent studies have underscored the productivity-enhancing effects of plastic mulching for rain-fed potatoes. However, the adaptability of mulching measures to climate change in order to facilitate increased potato yields remains a question. Moreover, the coupling effects of different climatic factors on potato production was unclear. ObjectiveThis study aimed to investigate the impact of different climatic factors and their coupling effects on the yields of mulching and no mulching potatoes in the Loess Plateau. MethodsWe utilized multiple crop models and global climate models (GCMs) to predict the yields of mulching and no mulching potatoes on the Loess Plateau based on Shared Socioeconomic Pathway (SSP) 245 and SSP585 scenarios. Additionally, we analyzed the response of yields to the coupling effects of climate, and clarified the effects of main climatic coupling effects to yield of mulching and no mulching potatoes. Results and conclusionsWe found that, for mulching potatoes, the contribution of climate coupling to yield under the SSP245 and SSP585 scenarios ranged from 47.05 % to 49.31 % for the period 2021–2060 and increased to 49.09 % to 50.94 % for the period 2061–2100. The mean temperature (Tmen)-dominated coupling contributed the most to yield for mulching potatoes, while for no mulching potatoes, precipitation (Pr)-dominated coupling played a dominant role. The maximum temperature (Tmax)-dominated coupling significantly reduced potato yields in the future, and mulching measures exacerbated the negative effect. However, mulching measures eliminated the adverse impact of minimum temperature (Tmin)-dominated coupling on potato yields. After decomposing the coupling effects of climatic factors, we found that the main factors leading to a reduction in potato yield were Tmax and Pr couplings, with mulching measures amplifying the heat-moisture effects. But mulching not only alleviated Tmin and Pr coupling but also strengthened the Tmean and Pr coupling, resulting in increased yield. SignificanceHence, understanding how mulching potatoes avoid heat-moisture coupling to promote production was crucial for the future on the Loess Plateau. Our findings contribute to clarifying the impact of climatic coupling on mulching potato production, thereby aiding in the informed development of rational policies.

Future climate risks to world cultural heritage sites in Spain: A systematic analysis based on shared socioeconomic pathways

Rapidly advancing anthropogenic climate change is a severe threat to cultural heritage worldwide. World cultural heritage sites (WCHS) are recognized by UNESCO as having outstanding international importance. Identifying and quantifying the impacts of climate change on the WCHS is therefore crucial for the development of long-term protection policies. Spain, the subject of the present study, is one of the most important world heritage countries in terms of the number of sites and is highly vulnerable to climate change under global scenarios.This study identified the main climate risks faced by Spain's WCHS on the basis of future climate data from four shared socioeconomic pathway (SSP) scenarios under the most recent version of the Coupled Model Intercomparison Project (CMIP6), the most up-to-date global climate model available. Risks include sea level rise and coastal flooding, fire risk and drought risk, hydrodynamic scouring and corrosion, and biodegradation. Some WCHS are located in regions that are projected to experience surface warming exceeding the global average by 2100 under the SSP5--8.5 scenario, with a doubling of extreme climate risk (a gradient from scenarios SSP1--2.6, SSP2--4.5, SSP3--7.0 to SSP5--8.5). Under this shared socioeconomic pathway, three Spanish WCHS are at risk of being submerged by seawater by 2100. On the basis of historical data, we identified greater potential fire risk in regions where Spain's WCHS is located than in other regions in Europe, with eight WCHS experiencing weather-induced fire hazards exceeding 95 %. Considering the combination of LUC types within the Spanish WCHS, we identified two WCHS that exemplify this risk: 1) the archaeological site of Atapuerca, which is primarily occupied by broad-leaved forest, and 2) the Caliphate city of Medina Azahara, which is surrounded by natural grasslands, emphasizing the need for fire prevention in woodland and grassland areas. Furthermore, we quantified the hydrodynamic scouring risk, corrosion and biodegradation risk, and drought risk in the entire region where Spain's WCHS are located from 2081 to 2100 and clustered them on the basis of risk characteristics. We found that under the SSP1-2.6 scenario, the overall pattern of climate risk faced by Spain's WCHS did not change significantly from the present, but there were clear changes under the SSP5-8.5 scenario. We also identified that Spain's WCHS listings are at greater risk from different climate risks. This study predicts the potential impact of climate change on Spain's WCHS, emphasizing the crucial role of “carbon neutrality” in reducing various climate risks to Spain's WCHS and providing guidance for the development of future long-term protection policies.