Convolutional conditional neural processes for local climate downscaling

A new model is presented for multisite statistical downscaling of temperature and precipitation using convolutional conditional neural processes (convCNPs). ConvCNPs are a recently developed class of models that allow deep-learning techniques to be applied to off-the-grid spatio-temporal data. In contrast to existing methods that map from low-resolution model output to high-resolution predictions at a discrete set of locations, this model outputs a stochastic process that can be queried at an arbitrary latitude–longitude coordinate. The convCNP model is shown to outperform an ensemble of existing downscaling techniques over Europe for both temperature and precipitation taken from the VALUE intercomparison project. The model also outperforms an approach that uses Gaussian processes to interpolate single-site downscaling models at unseen locations. Importantly, substantial improvement is seen in the representation of extreme precipitation events. These results indicate that the convCNP is a robust downscaling model suitable for generating localised projections for use in climate impact studies.

Climate change penalty and benefit on surface ozone: A global perspective based on CMIP6 earth system models

This work presents an analysis of the effect of climate change on surface ozone discussing the related penalties and benefits around the globe from the global modeling perspective based on simulations with five CMIP6 (Coupled Model Intercomparison Project Phase 6) Earth System Models. As part of AerChemMIP (Aerosol Chemistry Model Intercomparison Project) all models conducted simulation experiments considering future climate (ssp370SST) and present-day climate (ssp370pdSST) under the same future emissions trajectory (SSP3-7.0). A multi-model global average climate change benefit on surface ozone of -0.96±0.07 ppbv oC-1 is calculated which is mainly linked to the dominating role of enhanced ozone destruction with higher water vapour abudances under a warmer climate. Over regions remote from pollution sources, there is a robust decline in mean surface ozone concentration on an annual basis as well as for boreal winter and summer varying spatially from -0.2 to -2 ppbv oC-1, with strongest decline over tropical oceanic regions. The implication is that over regions remote from pollution sources (except over the Arctic) there is a consistent climate change benefit for baseline ozone due to global warming. However, ozone increases over regions close to anthropogenic pollution sources or close to enhanced natural Biogenic Volatile Organic Compounds (BVOC) emission sources with a rate ranging regionally from 0.2 to 2 ppbv oC-1, implying a regional surface ozone penalty due to global warming. Overall, the future climate change enhances the efficiency of precursor emissions to generate surface ozone in polluted regions and thus the magnitude of this effect depends on the regional emission changes considered in this study within the SSP3_7.0 scenario. The comparison of the climate change impact effect on surface ozone versus the combined effect of climate and emission changes indicates the dominant role of precursor emission changes in projecting surface ozone concentrations under future climate change scenarios.

The Variability of Air-sea O2 Flux in CMIP6: Implications for Estimating Terrestrial and Oceanic Carbon Sinks

The measurement of atmospheric O2 concentrations and related oxygen budget have been used to estimate terrestrial and oceanic carbon uptake. However, a discrepancy remains in assessments of O2 exchange between ocean and atmosphere (i.e. air-sea O2 flux), which is one of the major contributors to uncertainties in the O2-based estimations of the carbon uptake. Here, we explore the variability of air-sea O2 flux with the use of outputs from Coupled Model Intercomparison Project phase 6 (CMIP6). The simulated air-sea O2 flux exhibits an obvious warming-induced upward trend (∼1.49 Tmol yr−2) since the mid-1980s, accompanied by a strong decadal variability dominated by oceanic climate modes. We subsequently revise the O2-based carbon uptakes in response to this changing air-sea O2 flux. Our results show that, for the 1990–2000 period, the averaged net ocean and land sinks are 2.10±0.43 and 1.14±0.52 GtC yr−1 respectively, overall consistent with estimates derived by the Global Carbon Project (GCP). An enhanced carbon uptake is found in both land and ocean after year 2000, reflecting the modification of carbon cycle under human activities. Results derived from CMIP5 simulations also investigated in the study allow for comparisons from which we can see the vital importance of oxygen dataset on carbon uptake estimations.

CMIP6 simulations with the compact Earth system model OSCAR v3.1

While Earth system models (ESMs) are process-based and can be run at high resolutions, they are only limited by computational costs. Reduced complexity models, also called simple climate models or compact models, provide a much cheaper alternative, although at a loss of spatial information. Their structure relies on the sciences of the Earth system, but with a calibration against the most complex models. Therefore it remains important to evaluate and validate reduced complexity models. Here, we diagnose such a model the newest version of OSCAR (v3.1) using observations and results from ESMs from the current Coupled Model Intercomparison Project 6. A total of 99 experiments are selected for simulation with OSCAR v3.1 in a probabilistic framework, reaching a total of 567,700,000 simulated years. A first highlight of this exercise that the ocean carbon cycle of the model may diverge under some parametrizations and for high-warming scenarios. The diverging runs caused by this unstability were discarded in the post-processing. Then, each physical parametrization is weighted based on its performance against a set of observations, providing us with constrained results. Overall, OSCAR v3.1 shows good agreement with observations, ESMs and emerging properties. It qualitively reproduces the responses of complex ESMs, for all aspects of the Earth system. We observe some quantitative differences with these models, most of them being due to the observational constraints. Some specific features of OSCAR also contribute to these differences, such as its fully interactive atmospheric chemistry and endogenous calculations of biomass burning, wetlands CH4 and permafrost CH4 and CO2 emissions. The main points of improvements are a low sensitivity of the land carbon cycle to climate change, an unstability of the ocean carbon cycle, the seemingly too simple climate module, and the too strong climate feedback involving short-lived species. Beyond providing a key diagnosis of the OSCAR model in the context of the reduced-complexity models intercomparison project (RCMIP), this work is also meant to help with the upcoming calibration of OSCAR on CMIP6 results, and to provide a large group of CMIP6 simulations run consistently within a probabilistic framework.

Climate Projections Over Different Climatic Regions of Afghanistan for Shared Socioeconomic Scenarios

The global climate models (GCMs) of Coupled Model Intercomparison Project phase 6 (CMIP6) were used spatiotemporal projections of precipitation and temperature over Afghanistan for three shared socioeconomic pathways (SSP1-2.6, 2-4.5 and 5-8.5) and two future time horizons, early (2020-2059) and late (2060-2099). The Compromise Programming (CP) approach was employed to order the GCMs based on their skill to replicate precipitation and temperature climatology for the reference period (1975-2014). Three models, namely ACCESS-CM2, MPI-ESM1-2-LR, and FIO-ESM-2-0, showed the highest skill in simulating all three variables, and therefore, were chosen for the future projections. The ensemble mean of the GCMs showed an increase in maximum temperature by 1.5-2.5oC, 2.7-4.3 oC, and 4.5-5.3 oC and minimum temperature by 1.3-1.8 oC, 2.2-3.5 oC, and 4.6-5.2 oC for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively in the later period. Meanwhile, the changes in precipitation in the range of -15-18%, -36-47% and -40-68% for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The temperature and precipitation were projected to increase in the highlands and decrease over the deserts, indicating dry regions would be drier and wet regions wetter.

Köppen–Geiger Climate Clasification in the Pannonian basin According to SSP5-8.5 Scenario

The Köppen–Geiger climate classification is used to determine climate types in region of Pannonian Basin with data from the sixth phase of the Coupled Model Intercomparison Project. The study covers a period from years 2021 until 2100, and it shows how certain climate types are changing in percentage in thirty-year averages for six periods. In the period 1960-1990 years of the last century, the dominant climate type was warm summer humid continental climate (Dfb) with 98% presences in the region. The results show that the change of this climate type to the humid subtropical climate type (Cfa) began in the first half of the 21st century. The complete dominance of humid subtropical climate type in the most areas of the Pannonian Basin characterized the second half of the 21st century. Also, results show creation of a warm summer Mediterranean climate type (Csa), which according to certain simulations, is present from 10% to 30% on average in the region. In the central part of the region, a cold desert climate type (Bsk) was formed with approximately 6% presences in the region. This creation of climate types in some parts of the region shows that in the second half of 21st century drier and a warmer climate is expected compared to the last century.

Uncertainties in projected surface mass balance over the polar ice sheets from dynamically downscaled EC-Earth models

The future rates of ice sheet melt in Greenland and Antarctica are an important factor when making estimates of the likely rate of sea level rise. Global climate models that took part in the fifth Coupled Model Intercomparison Project (CMIP5) have generally been unable to replicate observed rates of ice sheet melt. With the advent of the sixth Coupled Model Intercomparison Project (CMIP6), with a general increase in the equilibrium climate sensitivity, we here compare two versions of the global climate model EC-Earth using the regional climate model HIRHAM5 downscaling of EC-Earth for Greenland and Antarctica. One version (v2) of EC-Earth is taken from CMIP5 for the high-emissions Representative Concentration Pathway 8.5 (RCP8.5) scenario and the other (v3) from CMIP6 for the comparable high-emissions Shared Socioeconomic Pathway 5-8.5 (SSP5-8.5) scenario. For Greenland, we downscale the two versions of EC-Earth for the historical period 1991–2010 and for the scenario period 2081–2100. For Antarctica, the periods are 1971–2000 and 2071–2100, respectively. For the Greenland Ice Sheet, we find that the mean change in temperature is 5.9 ∘C when downscaling EC-Earth v2 and 6.8 ∘C when downscaling EC-Earth v3. Corresponding values for Antarctica are 4.1 ∘C for v2 and 4.8 ∘C for v3. The mean change in surface mass balance at the end of the century under these high-emissions scenarios is found to be −290 Gt yr−1 (v2) and −1640 Gt yr−1 (v3) for Greenland and 420 Gt yr−1 (v2) and 80 Gt yr−1 (v3) for Antarctica. These distinct differences in temperature change and particularly surface mass balance change are a result of the higher equilibrium climate sensitivity in EC-Earth v3 (4.3 K) compared with 3.3 K in EC-Earth v2 and the differences in greenhouse gas concentrations between the RCP8.5 and the SSP5-8.5 scenarios.

ASSESSMENT OF THE QUALITY OF SIMULATION OF CHANGES OF THE DOWNWELLING SHORTWAVE RADIATION IN THE SEVASTOPOL REGION USING THE CMIP6 MODELS

Using the data of the Coupled Model Intercomparison Project 6 (CMIP6), the quality of the simulation of the observed climate changes of downwelling shortwave radiation in the Sevastopol region for the period 1983–2012 is assessed. It is shown that the average values of the considered characteristics of solar resources according to the data of climate models are, in general, higher than according to the ob-servational data, whereas the values of the standard deviation are lower. The analysis of linear trends of the downwelling shortwave radiation show that most climate models from the CMIP6 project correctly simulate the process up to the sign of the linear trend. Using a number of statistical characteristics, mod-els have been determined that best simulate the analyzed climatic characteristic and will be suitable for assessing future changes in the solar energy potential in the Sevastopol region.

Mass loss of the Antarctic ice sheet until the year 3000 under a sustained late-21st-century climate

Ice-sheet simulations of Antarctica extending to the year 3000 are analysed to investigate the long-term impacts of 21st-century warming. Climate projections are used as forcing until 2100 and afterwards no climate trend is applied. Fourteen experiments are for the ‘unabated warming’ pathway, and three are for the ‘reduced emissions’ pathway. For the unabated warming path simulations, West Antarctica suffers a much more severe ice loss than East Antarctica. In these cases, the mass loss amounts to an ensemble average of ~3.5 m sea-level equivalent (SLE) by the year 3000 and ~5.3 m for the most sensitive experiment. Four phases of mass loss occur during the collapse of the West Antarctic ice sheet. For the reduced emissions pathway, the mean mass loss is ~0.24 m SLE. By demonstrating that the consequences of the 21st century unabated warming path forcing are large and long term, the results present a different perspective to ISMIP6 (Ice Sheet Model Intercomparison Project for CMIP6). Extended ABUMIP (Antarctic BUttressing Model Intercomparison Project) simulations, assuming sudden and sustained ice-shelf collapse, with and without bedrock rebound, corroborate a negative feedback for ice loss found in previous studies, where bedrock rebound acts to slow the rate of ice loss.

Potenciales áreas cultivables de pasifloras en una región tropical considerando escenarios de cambio climático

Contextualización: El cambio climático y las actividades antrópicas sobre los recursos naturales se constituyen como los principales causantes de la pérdida de biodiversidad y la redistribución de las especies. Vacío de conocimiento: Sin embargo, los efectos a nivel de comunidades y ecosistemas, así como los impactos en cultivos agrícolas en escala regional, son poco estudiados. Los modelos de distribución de especies se han convertido, por lo tanto, en valiosas herramientas para la predicción de áreas potencialmente aptas para especies cultivables, su gestión y planificación. Propósito: Este estudio consistió en la predicción de potenciales áreas cultivables de maracuyá (Passiflora edulis var. flavicarpa Degener), granadilla (Passiflora ligularis Juss), y cholupa (Passiflora maliformis L.) en una región tropical, a través del modelo MaxEnt, en escenarios de cambio climático. Metodología: Se utilizaron como datos de entrada (para el modelo MaxEnt) registros de presencia de las especies analizadas, obtenidos a partir de sus coordenadas geográficas. En total, fueron usados 141 registros de presencia de maracuyá, 256 registros de granadilla y 40 registros de cholupa, así como 12 variables bioclimáticas para las proyecciones actuales y futuras en los periodos 2050 y 2070, considerando así dos escenarios RCPs (Representative Concentration Pathways) del Coupled Model Intercomparison Project (CMIP5) (RCP 4.5 y RCP 8.5). Resultados y conclusiones: Los resultados revelan que las potenciales áreas cultivables para las especies analizadas podrían pronosticarse a través de MaxEnt utilizando registros de presencia en campo y variables bioclimáticas. Así mismo, las simulaciones indicaron que las áreas de ocurrencia potencial para las especies analizadas podrían disminuir en el futuro dependiendo de los escenarios climáticos (RCP 4.5 y RCP 8.5) para los periodos 2050 y 2070. Para los cultivos de maracuyá, granadilla y cholupa, las mayores reducciones en las áreas de ocurrencia potencial corresponden al 23 %, 25 % y 31 % respectivamente, y se presentarían en el período 2070 en un escenario pesimista (RCP 8.5). Este es el primer estudio que pronostica las potenciales áreas cultivables de pasifloras utilizando el modelo Maxent y escenarios de cambio climático en escala regional en una región tropical. El abordaje propuesto puede proveer importantes herramientas para la gestión y aprovechamiento sostenible de las especies estudiadas.