Projections Of Future Climate Change Research Articles

Current states and future projections of climate change—Changes in water cycle due to global warming

Current states and future projections of climate change—Changes in water cycle due to global warming

How is science making its way into national climate change adaptation policy? Insights from Burkina Faso

ABSTRACT Burkina Faso is highly vulnerable to the increasing impacts of climate change and currently has large adaptation deficits. To improve adaptation planning at the national level, policies must, among other things, be informed by the current observed state of the environment as well as the best available projections of future climate change impacts. Scientific information has gradually been making its way into policies since 2007 but barriers still hinder the climate science-adaptation policy interface. A systematic policy document analysis, semi-structured interviews and participant observations were undertaken to explore how scientific information makes its way into national adaptation policy documents from its production to its inclusion into policies. The results suggest that overall, national adaptation policies are only to a limited extent informed by scientific information, due to insufficient availability of information, limited human and technical capacity and lack of finance. This highlights the need to build up national technical capacities to produce the required scientific information, by inter alia prioritizing it within ministerial budgets, reducing the dependency on international technical and financial partners. Further policy recommendations include capacity building and continuous formal collaboration protocols between producers and users, to ensure that usable scientific information is structurally integrated into policy-making processes.

Simulating Potential Impacts of Future Climate Change on Post-Rainy Season Sorghum Yields in India

Given the wide use of the multi-climate model mean (MMM) for impact assessment studies, this work examines the fidelity of Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the features of Indian summer monsoons as well as the post-rainy seasons for assessing the possible impacts of climate change on post-rainy season sorghum crop yields across India. The MMM simulations captured the spatial patterns and annual cycles of rainfall and surface air temperatures. However, bias was observed in the precipitation amounts and daily rainfall intensity. The trends in the simulations of MMM for both precipitation and temperatures were less satisfactory than the observed climate means. The Crop Environment Resource Synthesis (CERES)-sorghum model was used to estimate the potential impacts of future climate change on post-rainy season sorghum yield values. On average, post-rainy season sorghum yields are projected to vary between −4% and +40% as well as +10% and +59% in the near future (2040–2069) for RCP 4.5 and RCP 8.5, respectively, and between +20% and +70% (RCP 4.5) as well as +38% and +89% (RCP 8.5) in the far future (2070–2099). Even though surface air temperatures are increasing in future climate change projections, the findings suggest that an increase in the post-rainy season sorghum yields was due to an increase in the rainfall amounts up to 23% and an increase in the atmospheric CO2 levels by the end of the 21st century. The results suggest that the projected climate change during the post-rainy season over India is an opportunity for smallholders to capitalize on the increase in rainfall amounts and further increase sorghum yields with appropriate crop management strategies.

Shifting Goalposts: Setting Restoration Targets for Waterbirds in the Murray-Darling Basin Under Climate Change

The Murray-Darling Basin (the Basin) is the largest river system in Australia, supplying about 40% of the country’s irrigated agricultural output. Associated water resource development has come with a heavy price for the Basin’s freshwater ecosystems degrading them over decades. Australian governments are attempting to achieve environmental sustainability by returning water to the environment through buy-back of irrigation licences and improved water efficiencies. To determine effectiveness, basin-wide management objectives were established for key indicators, including waterbird populations and life histories which can effectively indicate ecosystem function and condition, driven by flow and flooding regimes. Ongoing monitoring of waterbird numbers indicates continued declines. We evaluated the feasibility of meeting established waterbird objectives under existing and predicted climates. We modelled long-term waterbird numbers using one of the world’s largest ongoing waterbird surveys (1983–2020), covering about 13.5% of the area of the entire Basin. Our findings suggest that under near future climate change projections, waterbird numbers will likely continue to decline, and remain below restoration targets set for the Basin. We discuss the current policy settings for using environmental water to support waterbird populations, recommending adjustments to restore the Basin’s waterbird populations and their wetlands in order to meet Australia’s conservation targets in relation to the ongoing global crisis of biodiversity loss.

Assessing the importance of bi-directional melting when modeling boreal peatland freeze/thaw dynamics

The modeling of seasonal ground ice (SGI) freeze/thaw a common feature in boreal peatlands, has often been completed using a unidirectional approach, where melting is driven by energy inputs from the surface. However, bi-directional melt is known to occur, and can potentially increase the spring melt rate. Accurate modelling of the timing of ice-free conditions in peatlands is important because SGI can impede spring infiltration and lead to substantial spring snowmelt runoff from peatlands. However, when modelling melt only from above, erroneous results in the model estimation of ice-free conditions can occur, which can lead to knock on-effects for modelling peatland hydrological function. Furthermore, as the climate warms, it is unclear how this role of SGI may change in the future. This study used the Stefan Equation to model unidirectional and bi-directional melt to assess which performed better in modelling the timing of ice-free conditions compared to observed values (BI: 3.9 ± 2.1 days, UNI: 9.0 ± 4.7). Including bi-directional melt improved model performance by reducing this difference by approximately 5 days. Model performance for SGI freeze/thaw cycles were similar, with BI being slightly more accurate in freezing (RMSE:2.7 cm versus 3.3 cm) and melting (RMSE: 2.6 cm vs 3.7 cm) compared to the unidirectional approach. While the model improvement in the timing of ice-free conditions was substantial, careful consideration is needed in determining when a peatland is functionally ice free in future modelling studies. The Stefan Equation was found to be most sensitive to changes in soil moisture, compared to ground surface temperature and peat porosity, likely due to the relationship between thermal conductivity and frozen and liquid water content. Comparisons with future climate change projections suggest that the timing of ice-free conditions could shift by as much as 2 weeks earlier in the 2050′s and by almost a month earlier in the 2080′s. However, the timing of snowfall, and rain on snow events continues to be a source of model uncertainty. Future studies should work to investigate the potential positive feedbacks this could create. In conclusion, the Stefan Equation presents a relatively easy path for incorporating bi-directional melt into peatland models. This process should be included in peatland ecohydrological models in order to properly model the timing of melt and ice-free conditions.

Improved summer daily and sub-daily precipitation over Eastern China in convection-permitting simulations

Based on the long-term (1998–2007) regional climate simulations using the Weather Research and Forecasting (WRF) model with three different horizontal resolutions (36 km, 12 km and 4 km), this work examines the improvement of convection-permitting regional climate model (CP RCM) in simulating the daily and sub-daily precipitation over eastern China. CP RCM produces more reliable mean precipitation and more realistic wet day frequency as well as better low-level wind and moisture than those in the convection-parameterized counterpart. Due to the more realistic surface heterogeneities, CP RCM distinctly improves the representation of hourly precipitation by increasing the occurrence of high-intensity precipitation compared to the 36-km and 12-km simulations, especially over areas with complex topography. Moreover, the improvement of diurnal variation of low-level wind direction and moisture convergence also coincides with the more reasonable diurnal amplitude and nocturnal precipitation in CP RCM as compared to the 12-km and 36-km simulations. Because of the better depiction of convection and its interaction with large-scale motions, CP RCM has a clear advantage in reproducing low-level wind and moisture, which lead to the better reproduced sub-daily precipitation. This study provides greater confidence in the projection of future climate change using CP RCM.

Sensitivity of Riparian Buffer Designs to Climate Change-Nutrient and Sediment Loading to Streams: A Case Study in the Albemarle-Pamlico River Basins (USA) Using HAWQS.

Riparian buffer zones (RBZs) provide multiple benefits to watershed ecosystems. We aimed to conduct an extensive sensitivity analysis of the RBZ designs to climate change nutrient and sediment loadings to streams. We designed 135 simulation scenarios starting with the six baselines RBZs (grass, urban, two-zone forest, three-zone forest, wildlife, and naturalized) in three 12-digit Hydrologic Unit Code watersheds within the Albemarle-Pamlico river basin (USA). Using the hydrologic and water quality system (HAWQS), we assessed the sensitivity of the designs to five water quality indicator (WQI) parameters: dissolved oxygen (DO), total phosphorous (TP), total nitrogen (TN), sediment (SD), and biochemical oxygen demand (BD). To understand the climate mitigation potential of RBZs, we identified a subset of future climate change projection models of air temperature and precipitation using EPA's Locating and Selecting Scenarios Online tool. Analyses revealed optimal RBZ designs for the three watersheds. In terms of watershed ecosystem services sustainability, the optimal Urban RBZ in contemporary climate (1983-2018) reduced SD from 61-96%, TN from 34-55%, TP from 9-48%, and BD from 53-99%, and raised DO from 4-10% with respect to No-RBZ in the three watersheds. The late century's (2070-2099) extreme mean annual climate changes significantly increased the projected SD and BD; however, the addition of urban RBZs was projected to offset the climate change reducing SD from 28-94% and BD from 69-93% in the watersheds. All other types of RBZs are also projected to fully mitigate the climate change impacts on WQI parameters except three-zone RBZ.

Assessing future vulnerability and risk of humanitarian crises using climate change and population projections within the INFORM framework

INFORM Risk Index is a global indicator-based disaster risk assessment tool that combines hazards, exposure, vulnerability and lack of coping capacity indicators with the purpose to support humanitarian crisis management decisions considering the current climate and population. In this exploratory study, we extend the Index to include future climate change and population projections using RCP 8.5 climate projections of coastal flood, river flood and drought, and SSP3 and SSP5 population projections for the period 2036 to 2065. For the three hazards considered, annually 1.3 billion people (150% increase), 1.8 billion people (249% increase) and 1.5 billion people (197% increase) in the mid-21st century are projected to be exposed under the 2015, SSP3 and SSP5 population estimates, respectively. Drought shows the highest exposure levels followed by river flood and then coastal flood, with some regional differences. The largest exposed population is projected in Asia, while the largest percent changes are projected in Africa and Oceania. Countries with largest current and projected risk including non-climatic factors are generally located in Africa, West and South Asia and Central America. An uncertainty analysis of the extended index shows that it is generally robust and not influenced by the methodological choices. The projected changes in risk and coping capacity (vulnerability) due to climate change are generally greater than those associated with population changes. Countries in Europe, Western and Northern Asia and Africa tend to show higher reduction levels in vulnerability (lack of coping capacity) required to nullify the adverse impacts of the projected amplified hazards and exposure. The required increase in coping capacity (decreased vulnerability) can inform decision-making processes on disaster risk reduction and adaptation options to maintain manageable risk levels at global and national scale. Overall, the extended INFORM Risk Index is a means to integrate Disaster Risk Reduction and Climate Change Adaptation policy agendas to create conditions for greater policy impact, more efficient use of resources and more effective action in protecting life, livelihoods and valuable assets.

Environmental variability at the margin of the South American monsoon system recorded by a high-resolution sediment record from Lagoa Dourada (South Brazil)

High-resolution geochemical and sedimentological data have been obtained for a lacustrine sediment record from Lagoa Dourada (South Brazil). Four distinctly different depositional processes were determined: (1) Suspension fallout of fine-grained minerogenic particles transferred via fluvial activity dominates the Early Holocene and relates to open grassland in the catchment area; (2) Activation of the karst hydrological system with deposition of massive sand layers indicates increased precipitation at the onset of the Middle Holocene; (3) Minerogenic sediments are replaced by organic deposition due to wetter climatic conditions with the expansion of woodlands in combination with release of dissolved nutrients due to enhanced pedogenesis during the Middle to Late Holocene; (4) Human-induced land-use change caused destabilization of soils in the catchment area with resulting cultural soil erosion between 1800 and 1950 CE. These depositional trends are linked to intensity variations of the South American Monsoon System (SAMS). Century-long climatic events detected by data of high-resolution XRF scanning confirm this relationship and provide signals of the 8.2 and 4.2 ka events as well as of the Little Ice Age. These events document increased rainfall with complex responses of the environmental system. Our SAMS-induced consequences of past hydroclimatic variability on the environment of South Brazil provide background information for better evaluating model projections of future climate change.

S2P3-R v2.0: computationally efficient modelling of shelf seas on regional to global scales

Abstract. The marine impacts of climate change on our societies will be largely felt through coastal waters and shelf seas. These impacts involve sectors as diverse as tourism, fisheries and energy production. Projections of future marine climate change come from global models. Modelling at the global scale is required to capture the feedbacks and large-scale transport of physical properties such as heat, which occur within the climate system, but global models currently cannot provide detail in the shelf seas. Version 2 of the regional implementation of the Shelf Sea Physics and Primary Production (S2P3-R v2.0) model bridges the gap between global projections and local shelf-sea impacts. S2P3-R v2.0 is a highly simplified coastal shelf model, computationally efficient enough to be run across the shelf seas of the whole globe. Despite the simplified nature of the model, it can display regional skill comparable to state-of-the-art models, and at the scale of the global (excluding high latitudes) shelf seas it can explain >50 % of the interannual sea surface temperature (SST) variability in ∼60 % of grid cells and >80 % of interannual variability in ∼20 % of grid cells. The model can be run at any resolution for which the input data can be supplied, without expert technical knowledge, and using a modest off-the-shelf computer. The accessibility of S2P3-R v2.0 places it within reach of an array of coastal managers and policy makers, allowing it to be run routinely once set up and evaluated for a region under expert guidance. The computational efficiency and relative scientific simplicity of the tool make it ideally suited to educational applications. S2P3-R v2.0 is set up to be driven directly with output from reanalysis products or daily atmospheric output from climate models such as those which contribute to the sixth phase of the Climate Model Intercomparison Project, making it a valuable tool for semi-dynamical downscaling of climate projections. The updates introduced into version 2.0 of this model are primarily focused around the ability to geographical relocate the model, model usability and speed but also scientific improvements. The value of this model comes from its computational efficiency, which necessitates simplicity. This simplicity leads to several limitations, which are discussed in the context of evaluation at regional and global scales.

Mitigation and adaptation of climate change disaster

Climate change is a long-term change in the statistical distribution of weather patterns over time periods ranging from decades to millions of years. It can also be interpreted as a shift in average weather conditions or a change in the distribution of average weather events. Climate change can occur locally, in specific regions, or across the entire planet’s surface. This change is characterized by at least four characteristics:, first rising global temperature, second rising sea levels, third extreme weather conditions and others, and four changes in rainfall patterns. Climate change is currently marked by an increase in the frequency of hydrometeorological disasters, such as decreased water availability and or even excess water discharge at other times, as well as forest and land fires. Based on future climate change projections, these hydrometeorological disasters have the potential to worsen threathening the resilience of water, food, and energy resources. Climate change is frequently associated with disaster due to an increase in hydrometeorological events over time. However, climate change is not the only cause. The disaster impacts are the results and indicators of more complex issues caused by larger environmental, social changes, and economic changes. These various disaster challenges in the future will necessitate earlier anticipatory preparations so that Indonesia and the rest of the world can adapt and mitigate appropriately.

Modeling Impact of Climate Change on Surface Water Availability Using SWAT Model in a Semi-Arid Basin: Case of El Kalb River, Lebanon

Assessing the impact of climate change on streamflow is crucial for depicting the vulnerability of water resources and for identifying proper adaptation measures. This study used the Soil and Water Assessment Tool (SWAT) to simulate the impact of climate change on the streamflow of El Kalb river, a major perennial river in Lebanon. The model performance was tested for monthly flow at two stations under a nine-year calibration period (2003–2011) and a four-year validation period (2012–2015). The model results indicated satisfactory precision in fitting observed and simulated flow using various acceptable statistical indices. Future projections of climate change were obtained for three Representative Concentration Pathways (RCPs) (2.6, 4.5, and 8.5). The model indicated that the average annual discharge of El Kalb River in the near future (2021–2040) will decrease by around 28–29% under the three RCP scenarios. End-of-century projections (2081–2100) indicated that the flow will decrease by 23%, 28%, and 45% under RCP 2.6, RCP 4.5, and RCP 8.5, respectively.

Sugarcane yield future scenarios in Brazil as projected by the APSIM-Sugar model

Crop models like APSIM-Sugar have been used to assess the impacts of climate variability and change on sugarcane. APSIM-Sugar was recently upgraded to simulate sugarcane in Brazil and to cater for climate impacts under water-limited environments. In this context, our first objective was to evaluate the recent upgrade on determined traits for the most cultivated Brazilian variety under water-limited conditions. As a second objective, we applied these model settings to project the sugarcane crop performance under likely changing climates in important producing regions. The stalk mass estimates for four published experiments across Brazil were satisfactory, with a R2 of 0.96, the agreement d index of 0.99, and root mean square error (RMSE) of 3.8 t/ha. Future climate projections (until 2099), considered two emission scenarios (RCP4.5 and RCP8.5), were derived based on a recently proposed subset approach of five climate models (GCMs) from CMIP5. The subset aimed to capture the full ensemble of temperature and rainfall changes by considering basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry). A typical system with 12-month old crops was simulated for rainfed and irrigated sites. The ensemble of future projections indicated that cane yields would decline compared to the present average simulations (1980−2009) for rainfed sites, mainly due to increased water stress. Yields at fully irrigated sites are also projected to decline slightly. However, the expected changes were highly variable between GCMs with the End-of-Century period presenting large uncertainty. In short, while providing an up-to-date projection of future climate change impacts on sugarcane in Brazil, such results should be interpreted with caution.

Severe Convective Wind Environments and Future Projected Changes in Australia

AbstractThunderstorms can produce severe convective winds (SCWs) that damage buildings and other infrastructure such as electricity transmission towers. Understanding the climatology of SCWs is therefore important for planning and risk management. An archive of observed SCWs is used to examine a diverse set of diagnostics for indicating SCW environments based on reanalysis data. These diagnostics are then applied to climate model data to examine projections of future climate change for Australia. A diagnostic based on logistic regression is found to provide a better representation of observed SCW occurrences than other diagnostics. Projections for the future based on that diagnostic indicate increases and decreases between −16% and 34% in the occurrence frequency of regionally averaged SCW environments, based on the 10th and 90th percentile estimates of annual mean changes from a 12‐member ensemble of global climate models. Projections based on other severe weather diagnostics indicate a wider range of future changes, including increases and decreases of up to 50% in magnitude, with regional and seasonal variations through Australia. Changes in the frequency of SCW environments appears to be largely driven by increased low level moisture concentrations which can lead to increased convective available potential energy, countered in some cases by a stabilization of the mid‐troposphere temperature lapse rate. These results represent the most comprehensive estimate to date for constraining the range of uncertainty in projected future changes in convective environments for Australia, including severe thunderstorms and associated SCWs, noting that this has significant implications for risk management and climate adaptation purposes.

Diversified pastures at the front line of climate change in Northland: farmers experiences, new directions and wider implications for other parts of the country

The persistence of both perennial ryegrass and white clover is challenged under summer-dry conditions. Future climate change projections indicate greater incidence and severity of summer moisture stress for many regions in New Zealand, and therefore, greater pressure on our traditional pasture base. The ‘Northland Diversified Forages Project’ aimed to identify alternative pasture species that provide an advantage in terms of dry matter yield, quality and/or timing of growth within a summer-dry environment, with a particular focus on legumes. A series of mown-plot trial and paddock demonstrations were established across a range of soil types to assess the potential of a wide variety of forage species. Perennial ryegrass and white clover both failed to persist, comprising less than 25% of the sward within 3 years of establishment. Cocksfoot demonstrated potential as a more persistent alternative to perennial ryegrass. However, whilst a range of legumes were successful at increasing the proportion of legume in the sward and total yield in the first year, significant challenges were identified in maintaining functional legumes across multiple years. This raises questions around whether we currently have the right species in New Zealand to adapt to a changing climate.

Climate change impacts and uncertainty on spatiotemporal variations of drought indices for an irrigated catchment

Droughts are responsible for severe vegetation loss and declining agricultural yields. As future climate change projections imply an increased risk of extreme events, the occurrence of droughts is potentially accelerating in the future. The influence of climate change on drought events in a Danish agricultural catchment under the emission scenario RCP8.5 are evaluated by three different drought indices covering soil moisture, groundwater and streamflow deficits. The indices are based on results from a hydrological model forced by downscaled climate outputs from 16 Euro-CORDEX climate models (GCM-RCMs), while considering uncertainties among climate model projections. The hydrological model demonstrated a satisfactory ability in modelling historical drought characteristics. The results from the future projections showed that the intensity and frequency of droughts increased towards the end of the century. The spatial patterns of changes in drought were found to be highly dependent on the climate model results, index formulations and assumptions, as well as the hydrogeological properties of the catchment. Groundwater based irrigation in the agricultural areas effectively mitigates soil moisture drought, leading to lower future uncertainty of the ensemble mean (higher model agreement) for soil moisture droughts at irrigated locations. This is obtained at the cost of lower groundwater levels in both reference and future periods resulting in larger uncertainties on the simulated groundwater droughts, because of the addition of irrigation uncertainty. While the joint impact of greater groundwater abstraction and changing dynamics of precipitation and groundwater recharge also leads to larger streamflow variability between model combinations (standard deviation) under RCP8.5 for the downstream discharge station.

Adaptive ecological niche migration does not negate extinction susceptibility

Extinction rates in the modern world are currently at their highest in 66 million years and are likely to increase with projections of future climate change. Our knowledge of modern-day extinction risk is largely limited to decadal-centennial terrestrial records, while data from the marine realm is typically applied to high-order (> 1 million year) timescales. At present, it is unclear whether fossil organisms with common ancestry and ecological niche exhibit consistent indicators of ecological stress prior to extinction. The marine microfossil record, specifically that of the planktonic foraminifera, allows for high-resolution analyses of large numbers of fossil individuals with incredibly well-established ecological and phylogenetic history. Here, analysis of the isochronous extinction of two members of the planktonic foraminiferal genus Dentoglobigerina shows disruptive selection differentially compounded by permanent ecological niche migration, “pre-extinction gigantism”, and photosymbiont bleaching prior to extinction. Despite shared ecological and phylogenetic affinity, and timing of extinction, the marked discrepancies observed within the pre-extinction phenotypic responses are species-specific. These behaviours may provide insights into the nature of evolution and extinction in the open ocean and can potentially assist in the recognition and understanding of marine extinction risk in response to global climate change.

An Analysis of (Sub-)Hourly Rainfall in Convection-Permitting Climate Simulations Over Southern Sweden From a User’s Perspective

To date, the assessment of hydrological climate change impacts, not least on pluvial flooding, has been severely limited by i) the insufficient spatial resolution of regional climate models (RCMs) as well as ii) the simplified description of key processes, e.g., convective rainfall generation. Therefore, expectations have been high on the recent generation of high-resolution convection-permitting regional climate models (CPRCMs), to reproduce the small-scale features of observed (extreme) rainfall that are driving small-scale hydrological hazards. Are they living up to these expectations? In this study, we zoom in on southern Sweden and investigate to which extent two climate models, a 3-km resolution CPRCM (HCLIM3) and a 12-km non-convection permitting RCM (HCLIM12), are able to reproduce the rainfall climate with focus on short-duration extremes. We use three types of evaluation–intensity-based, time-based and event-based–which have been designed to provide an added value to users of high-intensity rainfall information, as compared with the ways climate models are generally evaluated. In particular, in the event-based evaluation we explore the prospect of bringing climate model evaluation closer to the user by investigating whether the models are able to reproduce a well-known historical high-intensity rainfall event in the city of Malmö 2014. The results very clearly point at a substantially reduced bias in HCLIM3 as compared with HCLIM12, especially for short-duration extremes, as well as an overall better reproduction of the diurnal cycles. Furthermore, the HCLIM3 model proved able to generate events similar to the one in Malmö 2014. The results imply that CPRCMs offer a clear potential for increased confidence in future projections of small-scale hydrological climate change impacts, which is crucial for climate-proofing, e.g., our cities, as well as climate modeling in general.

On the suitability of deep convolutional neural networks for continental-wide downscaling of climate change projections

In a recent paper, Baño-Medina et al. (Configuration and Intercomparison of deep learning neural models for statistical downscaling. preprint, 2019) assessed the suitability of deep convolutional neural networks (CNNs) for downscaling of temperature and precipitation over Europe using large-scale ‘perfect’ reanalysis predictors. They compared the results provided by CNNs with those obtained from a set of standard methods which have been traditionally used for downscaling purposes (linear and generalized linear models), concluding that CNNs are well suited for continental-wide applications. That analysis is extended here by assessing the suitability of CNNs for downscaling future climate change projections using Global Climate Model (GCM) outputs as predictors. This is particularly relevant for this type of “black-box” models, whose results cannot be easily explained based on physical reasons and could potentially lead to implausible downscaled projections due to uncontrolled extrapolation artifacts. Based on this premise, we analyze in this work the two key assumptions that are made in perfect prognosis downscaling: (1) the predictors chosen to build the statistical model should be well reproduced by GCMs and (2) the statistical model should be able to reliably extrapolate out of sample (climate change) conditions. As a first step to test the suitability of these models, the latter assumption is assessed here by analyzing how the CNNs affect the raw GCM climate change signal (defined as the difference, or delta, between future and historical climate). Our results show that, as compared to well-established generalized linear models (GLMs), CNNs yield smaller departures from the raw GCM outputs for the end of century, resulting in more plausible downscaling results for climate change applications. Moreover, as a consequence of the automatic treatment of spatial features, CNNs are also found to provide more spatially homogeneous downscaled patterns than GLMs.

Reduced High-Latitude Land Seasonality in Climates with Very High Carbon Dioxide

AbstractObservations of warm past climates and projections of future climate change show that the Arctic warms more than the global mean, particularly during winter months. Previous work has attributed this reduced Arctic land seasonality to the effects of sea ice or clouds. In this paper, we show that the reduced Arctic land seasonality is a robust consequence of the relatively small surface heat capacity of land and the nonlinearity of the temperature dependence of surface longwave emission, without recourse to other processes or feedbacks. We use a General Circulation Model (GCM) with no clouds or sea ice and a simple representation of land. In the annual mean, the equator-to-pole surface temperature gradient falls with increasing CO2, but this is only a near-surface phenomenon and is not caused by the change in total meridional heat transport, which is virtually unaltered. The high-latitude land has about twice as much warming in winter than in summer, whereas high-latitude ocean has very little seasonality in warming. A surface energy balance model shows how the combination of the smaller surface heat capacity of land and the nonlinearity of the temperature dependence of surface longwave emission gives rise to the reduced seasonality of the land surface. The increase in evaporation over land also leads to winter amplification of warming over land, although amplification still occurs without it. While changes in clouds, sea ice, and ocean heat transport undoubtedly play a role in high-latitude warming, these results show that enhanced land surface temperature warming in winter can happen in their absence for robust reasons.