Projected Changes In Rainfall Research Articles

Modelling vegetation dynamics for future climates in Australian catchments: Comparison of a conceptual eco-hydrological modelling approach with a deep learning alternative

Dynamically simulating leaf area index assists in modelling the feedbacks between eco-hydrologic and climatic processes. The particular challenge for Australia is the prevalence of arid and semi-arid ecosystems where water availability plays a crucial role in vegetation productivity. To understand whether existing LAI models can capture plant dynamics under changing climates, we tested two competing models across Australia's different climate zones: a conceptual eco-hydrologic model that applies water use efficiency term to relate LAI to water uptake, and a deep learning approach. An initial virtual catchment experiment with deep learning showed that it only uses information from potential evapotranspiration. For future climates, the conceptual model captured a negative trend and increasing variance in LAI, which is plausible given projected rainfall changes, while deep learning did not. Our study demonstrated an example of ‘right answer for the wrong reasons’, and the importance of incorporating knowledge of water-carbon coupling for appropriate scenarios.

Potential for historically unprecedented Australian droughts from natural variability and climate change

Abstract. In drought-prone Australia, multi-year droughts have detrimental impacts on both the natural environment and human societies. For responsible water management, we need a thorough understanding of the full range of variability in multi-year droughts and how this might change in a warming world. But research into the long-term frequency, persistence, and severity of Australian droughts is limited. This is partly due to the length of the observational record, which is short relative to the timescales of hydroclimatic variability and hence may not capture the range of possible variability. Using simulations of Australian precipitation over the full past millennium (850–2000), we characterise the nature of multi-year meteorological droughts across Australia and include a particular focus on the Murray–Darling Basin (MDB), the largest agricultural region in Australia. We find that simulated Australian droughts in the 20th century (1900–2000) are within the bounds of pre-industrial natural variability in terms of drought intensity, severity, and frequency. A tendency for droughts to last longer in southwestern and eastern Australia (including the MDB) in the 20th century, compared with the pre-industrial period, suggests an emerging anthropogenic influence, consistent with projected rainfall changes in these regions. Large volcanic eruptions tend to promote drought-free intervals in the MDB. Model simulations of droughts over the last millennium suggest that future droughts across Australia could be much longer than what was experienced in the 20th century, even without any human influence. With the addition of anthropogenic climate change, which favours drought conditions across much of southern Australia due to reduced cool-season rainfall, it is likely that future droughts in Australia will exceed recent historical experience.

Dynamic and Thermodynamic Contributions to Late 21st Century Projected Rainfall Change in the Congo Basin: Impact of a Regional Climate Model’s Formulation

Addressing the impacts of climate change requires, first of all, understanding the mechanisms driving changes, especially at the regional scale. In particular, policymakers and other stakeholders need physically robust climate change information to drive societal responses to a changing climate. This study analyses late 21st-century (2071–2100) precipitation projections for the Congo Basin under representative concentration pathway (RCP) 8.5, using the Rossby Centre Regional Climate Model (RCM) RCA4. Specifically, we examine the impact of the RCM formulation (reduction of turbulent mixing) on future change in seasonal mean precipitation by comparing the results of the modified model version (RCA4-v4) with those of the standard version (RCA4-v1) used in CORDEX (Coordinated Regional Climate Downscaling Experiment). The two RCM versions are driven by two global climate models participating in the Coupled Model Intercomparison Project phase 5 (CMIP5). The results show that seasonal precipitation is largely affected by modifications in the atmospheric column moisture convergence or divergence, and, in turn, associated with changes in the dynamic (ΔDY) and thermodynamic (ΔTH) components of the moisture-budget equation. Projected decreased precipitation in the dry seasons (December–January–February and June–July–August) is linked to increased moisture divergence driven by dynamic effects (changes in circulation), with most experiments showing ΔDY as the main contributor (>60%) to the total moisture budget. Overall, precipitation is projected to increase in the wet seasons (March–April–May and September–October–November), which can be attributed to both dynamic and thermodynamic effects, but with a larger thermodynamic contribution (changes in specific humidity, ΔTH > 45%), compared to the dynamic one (ΔDY > 40%). Through a comparison of the two model versions, we found that the formulation (reducing turbulent mixing) and boundary conditions (driving GCM) strongly influence precipitation projections. This result holds substantial value for ensuring the fitness of models for future projections intended for decision-makers.

Assessing climate change impact on river flow extreme events in different climates of Iran using hybrid application of LARS-WG6 and rainfall-runoff modeling of deep learning

Climate change and its side effects on weather variables and water resources is one of the recent international concerns. This research aims to project future changes in weather variables due to climate change for different emission scenarios of RCP2.6, RCP4.5 and RCP8.5 to assess and compare climate change impact on river flow variation based on hybrid application of deep learning and LARS-WG6 in different climates of Iran (CSA: cold semi-arid; HT: humid temperate; CA: cold arid). For this purpose, best combination of daily rainfall and discharges data with different lags were selected as inputs in rainfall-runoff modeling using Convolutional Neural Networks (CNN) model. Predicted meteorological data by the LARS-WG6 in the future (2021-2040) were then used as inputs for the selected CNN model and consequently runoff was predicted. Obtained findings showed that projected rainfall changes in 2021-2040 compared to the base period in scenarios of RCP2.6, 4.5 and 8.5 will be +14, +11, +6% in CA, +8, +1, +2% in CSA and +3.7, -1, -2.6% in HT regions, respectively. Whereas, maximum discharge in CA climate in scenario RCP2.6 is projected to raise about 18%, in the HT climate shows a reduce of about 5% in RCP8.5 and in CSA will decrease by about 5% in RCP2.6. Considering the effect of climate as well as seasonal changes in each region on the amount and direction of the climate change impacts on meteorological and hydrologic variables changes, assessing climate change impact in each region is necessary to extract adaptation strategies in water resources management.

Western and Central Tropical Pacific Rainfall Response to Climate Change: Sensitivity to Projected Sea Surface Temperature Patterns

Abstract Rainfall projections from the Coupled Model Intercomparison Project (CMIP) models are strongly tied to projected sea surface temperature (SST) spatial patterns through the “warmer-gets-wetter” mechanism. While these models consistently project an enhanced equatorial warming, they, however, indicate much more uncertain changes in zonal SST gradients. That translates into large uncertainties on rainfall projections. Here, we force an atmospheric model with synthetic SSTs whose zonal SST gradient changes span the range of CMIP5 uncertainties in the presence and in the absence of the robust equatorially enhanced warming. Our results confirm that projected rainfall changes are dominated by the effect of circulation changes, which are tied to SST through the “warmer-gets-wetter” mechanism. We show that SPCZ rainfall changes are entirely driven by the uncertain zonal SST gradient changes. The western equatorial Pacific rainfall increase is largely controlled by the robust enhanced equatorial warming for modest zonal SST gradient changes. However, for larger values, the effect of the zonal SST gradient change on rainfall projections becomes dominant due to nonlinear interactions with the enhanced equatorial warming. Overall, our study demonstrates that uncertainties in the zonal SST gradient changes strongly contribute to uncertainties in rainfall projections over both the South Pacific convergence zone and western equatorial Pacific. It is thus critical to reduce these uncertainties to produce more robust precipitation estimates.

Projected rainfall changes and their implications for rainfed agriculture in northern Ghana

Projected rainfall changes and their implications for rainfed agriculture in northern Ghana

Adaptations toward Climate Risk: Challenges and Opportunities of the Upland Farmers in Ifugao, Philippines

AbstractThere has been an increasing concern over the threats posed by climate change to the conservation of UNESCO World Heritage Sites and Globally Important Agricultural Heritage Systems (GIAHS). However, the Ifugao Rice Terraces (IRT) have received limited attention with respect to climate change, considering it is one of the provinces in the Philippines highly at risk to temperature change, projected rainfall change, and combined climate and weather-related risks. It is therefore necessary to assess how the community perceives climate change and how they can cope up with these impacts. This study aimed to explore farmers’ perceptions, adaptation strategies, and barriers to climate change in the community of Batad Rice Terraces. A total of 114 out of 197 households, three focused group discussions, and five interviews with key stakeholders, including government officials and community leaders, were conducted in 2017 and 2018. The result showed that farmers have already observed the negative impacts of changing weather patterns, particularly in their agricultural production. The most common impacts observed were low rice yield, drought, and drying of rice plants due to unpredictable rainfall patterns and temperature increase. The top three most important adaptation strategies in the face of climate variability are all water-related. This shows that strong local government support is recommended to repair and maintain irrigation canals within the terraces. The salient climate change barriers identified by the farmers were access to climate information, inadequate farm labor, and lack of access to agricultural extension.

Projections of future meteorological drought events under representative concentration pathways (RCPs) of CMIP5 over Kenya, East Africa

Understanding future evolution of drought scenario across localized domains remains an imperative process in bid to adapt tailor suit innovative solutions to drought risks and their impacts. The present study examines drought events by characterizing the trend, intensity, severity and frequency based on Standardized Precipitation Index (SPI), over Kenya, East Africa for near future (2010–2039), mid-century (2040–2069), and late century (2070–2100). The study utilizes Multi-model mean ensemble (MME) of five selected regional climate models (RCMs). Further, the models are bias corrected based on a quantile mapping bias corrected algorithm in order to minimize possible bias for accurate projections. The changes in annual and seasonal precipitation over Kenya is examined in order to associate with changes in drought occurrence. Results demonstrate positive shift, indicating an increase in projected rainfall change during all the three timescales. Projections of possible future meteorological drought events under RCPs scenario over study locale was conducted using SPI. The results demonstrate relatively better performance of biased corrected MME derived from Rossby Centre regional climate model (RCA4) in simulating drought indices over the Kenya. The MME projections for drought duration show an increase in moderate drought incidences with fewer incidences of extreme events across the RCP4.5 and 8.5 scenarios respectively. However, the duration of occurrences varies from one region to another with most hotspots located around northeastern sides of the country. Examination of projected changes in drought frequency and severity depict an occurrence of severe to extreme drought incidences that are expected to intensify during the near future time slice while overall projections show that more wet scenarios is depicted, with fewer cases of drought expected to occur during mid and towards end of the century of projection period. The study calls for enactment of appropriate mitigation measures to cope with possible scenarios of drought risks over Kenya in the future.

Visualizations of Projected Rainfall Change in the United Kingdom: An Interview Study about User Perceptions

Stakeholders from public, private, and third sectors need to adapt to a changing climate. Communications about climate may be challenging, especially for audiences with limited climate expertise. Here, we study how such audience members perceive visualizations about projected future rainfall. In semi-structured interviews, we presented 24 participants from climate-conscious organizations across the UK with three prototypical visualizations about projected future rainfall, adopted from the probabilistic United Kingdom Climate Projections: (1) Maps displaying a central estimate and confidence intervals, (2) a line graph and boxplots displaying change over time and associated confidence intervals, and (3) a probability density function for distributions of rainfall change. We analyzed participants’ responses using “Thematic Analysis”. In our analysis, we identified features that facilitated understanding—such as colors, simple captions, and comparisons between different emission scenarios—and barriers that hindered understanding, such as unfamiliar acronyms and terminology, confusing usage of probabilistic estimates, and expressions of relative change in percentages. We integrate these findings with the interdisciplinary risk communication literature and suggest content-related and editorial strategies for effectively designing visualizations about uncertain climate projections for audiences with limited climate expertise. These strategies will help organizations such as National Met Services to effectively communicate about a changing climate.

Projected changes in rainfall and temperature over the Philippines from multiple dynamical downscaling models

AbstractTo help meet increasing demands for high‐resolution climate change projections in the Philippines, this study provides the results of multiple dynamically downscaled climate model simulations for projected changes in rainfall and temperature over the country by the mid‐21st century (2036–2065) relative to the baseline period (1971–2000), under the RCP8.5 scenario. The model‐simulated seasonal means of temperature, rainfall, and low‐level wind patterns were first compared with observations during the baseline period. Comparisons made between the model‐derived and APHRODITE observation‐based gridded temperature and rainfall data indicate that the dynamically downscaled simulations provide an overall improvement from their driving global climate models in capturing the spatial patterns of rainfall over the country, and the spatial and temporal characteristics of the country's mean temperature. Future climate projections show that the country's climate is expected to become warmer by the mid‐21st century, with a multi‐model ensemble mean increase of 1.2 to 1.9°C, relative to the baseline period, projected for many parts of the country and across most seasons. Slightly higher increases are projected during the country's hottest season, March–April–May. However, there are large differences in the models' projected rainfall changes by the mid‐21st century across seasons and regions. For most parts of the country, the multi‐model ensemble includes simulations that show increases and simulations that show decreases in rainfall. Nevertheless, there is a tendency of model projections towards wetter conditions over northern and central sections of the country (particularly in the December–January–February season) and drier conditions in the southern region of the country in almost all seasons. The results demonstrate the need for communities in the Philippines to adapt to a future warmer climate and prepare for a range of possible future changes in rainfall and temperature.

Projected future changes in mean precipitation over Thailand based on multi‐model regional climate simulations of CORDEX Southeast Asia

AbstractThis paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion).

Process-oriented assessment of RCA4 regional climate model projections over the Congo Basin under $$1.5 \ ^{\circ }{\text {C}}$$ 1.5 ∘ C and $$2 \ ^{\circ }{\text {C}}$$ 2 ∘ C global warming levels: influence of regional moisture fluxes

Understanding the processes responsible for precipitation and its future change is important to develop plausible and sustainable climate change adaptation strategies, especially in regions with few available observed data like Congo Basin (CB). This paper investigates the atmospheric circulation processes associated with climate model biases in CB rainfall, and explores drivers of projected rainfall changes. Here we use an ensemble of simulations from the Swedish Regional Climate Model (RCM) RCA4, driven by eight General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), for the $$1.5 \ ^{\circ }{\text {C}}$$ and $$2\ ^{\circ }{\text {C}}$$ global warming levels (GWLs), and under the representative concentration pathways (RCPs) 4.5 and 8.5. RCA4 captures reasonably well the observed patterns of CB rainfall seasonality, but shows dry biases independent of seasons and large scale driving atmospheric conditions. While simulations mimic observed peaks in transition seasons (March–May and September–November), the rain-belt is misplaced southward (northward) in December–February (June–August), reducing the latitudinal extent of rainfall. Moreover, ERA-Interim reanalysis driven RCM simulation and RCM–GCM combinations show similar results, indicating the dominance of systematic biases. Modelled dry biases are associated with dry upper-tropospheric layers, resulting from a western outflow stronger than the eastern inflow and related to the northern component of African Easterly Jet. From the analysis of the climate change signal, we found that regional scale responses to anthropogenic forcings vary across GWLs and seasons. Changes of rainfall and moisture divergence are correlated, with values higher in March–May than in September–November, and larger for global warming of $$2.0 \ ^{\circ }{\text {C}}$$ than at $$1.5 \ ^{\circ }{\text {C}}$$ . There is an increase of zonal moisture divergence fluxes in upper atmospheric layers ( $$> 700\,{\text {hPa}}$$ ) under RCP8.5 compared to RCP4.5. Moreover, it is found that additional warming of $$0.5 \ ^{\circ }{\text {C}}$$ will change the hydrological cycle and water availability in the CB, with potential to cause challenges to water resource management, agriculture, hydro-power generation, sanitation and ecosystems.

The role of topography on projected rainfall change in mid-latitude mountain regions

Change to precipitation in a warming climate holds many implications for water management into the future, and an enhancement of a precipitation decrease or increase on or around mountains would have numerous impacts. Here, an intermediate resolution regional climate model (RCM) ensemble projects enhanced precipitation decrease on the windward slopes of over many mid-latitude mountains in winter, consistent with theory and model studies of idealised mountain ranges. This ensemble projects that an increase in convective rainfall determines the sign of total rainfall change in many regions in summer, only some of which are on or near mountains such as the European Alps. These same projected changes are present in inland slopes of the Australian Alps compared to surrounding regions as simulated by three RCM ensembles (the intermediate resolution and two high resolution ensembles), which agree on an enhanced precipitation decrease on the windward slopes in winter and spring, as well as an enhanced precipitation increase in summer driven by an increase in convective rainfall. The ensembles disagree on an enhanced precipitation decrease in autumn. The results represent regional-scale added value in the climate change signal of projections from high resolution models in cooler seasons, but suggest that the specific model components such as convection schemes strongly influence projections of summer rainfall change. Confidence in the simulation of change in convective rainfall, or convection-permitting modelling may be needed to raise confidence in summer rainfall projections over mountains.

Projected Changes in Intra-Season Rainfall Characteristics in the Niger River Basin, West Africa

The magnitude and timing of seasonal rainfall is vitally important to the health and vitality of key agro-ecological and social-economic systems of the Niger River Basin. Given this unique context, knowledge concerning how climate change is likely to impact future rainfall characteristics and patterns is critically needed for adaptation and mitigation planning. Using nine ensemble bias-corrected climate model projection results under RCP4.5 and RCP8.5 (RCP—Representative Concentration Pathway) emissions scenarios at the mid-future time period, 2021/2025-2050 from the Coordinated Regional Climate Downscaling Experiments (CORDEX) dataset; this study provides a comprehensive analysis of the projected changes in rainfall characteristics in three agro-ecological zones of the Niger River Basin. The results show an increase in the average rainfall of about 5%, 10–20% and 10–15% for the Southern Guinea, Northern Guinea and Sahelian zones, respectively, relative to the baseline, 1981/1985–2005. On the other hand, the change in future rainfall intensities are largely significant and the frequency of rainfall at the low, heavy and extreme rainfall events in the future decrease at most locations in the Niger River Basin. The results also showed an increase in the frequency of moderate rainfall events at all locations in the basin. However, in the Northern Guinea and Sahel locations, there is an increase in the frequency of projected heavy and extreme rainfall events. The results reveal a shift in the future onset/cessation and a shortening of the duration of the rainy season in the basin. Specifically, the mean date of rainfall onset will be delayed by between 10 and 32 days. The mean onset of cessation will also be delayed by between 10 and 21 days. It is posited that the projected rainfall changes pose serious risks for food security of the region and may require changes in the cropping patterns and management.

Canopy dynamics of two climate-smart cassava varieties under drought in SW Nigeria

Cassava (Manihot esculenta) is a major staple in Nigeria and elsewhere in sub-Saharan Africa where it is grown without irrigation. However, the estimated yield gaps between those obtained on farmers’ fields (12Mgha-1) and on research stations (up to 60Mgha) remain high. There is also little information about yield determinants and the impacts of the dry season on growth, leaf area development, senescence, and biomass partitioning of the cassava plant and how these impacts vary between variety and with fertiliser application. Given projected changes in rainfall, we conducted a study to understand better the development of the crop as well as the growth response to water deficiency during the dry season. This was part of the “African Cassava Agronomy Initiative” sponsored by the Bill & Melinda Gates Foundation. The factorial experiment compared the responses of two drought-tolerant varieties of cassava (TMEB 419, IITA-TMS-IBA980581), to four different potassium fertiliser treatments (nil fertiliser, 75 kgNha-1 and 20 kg P ha-1 with 90, 135 or 180 kgKha-1 elemental application rates) and two different planting dates, replicated in four blocks and at two sites in South West Nigeria. Measurements over the dry season (October 2017 – February 2018) included biomass partitioning, light intensity and canopy interception with the aid of a ceptometer, leaf senescence and leaf area estimates. Preliminary observations show TMEB 419 with a taller stem and less dense canopy than IITATMS-IBA980581. Relationships between dry season response and yield in 2018 will be established allowing to optimise the planting time and fertiliser regime for each variety.

Future climate change enhances rainfall seasonality in a regional model of western Maritime Continent

In this study, future changes in rainfall due to global climate change are investigated over the western Maritime Continent based on dynamically downscaled climate projections using the MIT Regional Climate Model (MRCM) with 12 km horizontal resolution. A total of nine 30-year regional climate projections driven by multi-GCMs projections (CCSM4, MPI-ESM-MR and ACCESS1.0) under multi-scenarios of greenhouse gases emissions (Historical: 1976–2005, RCP4.5 and RCP8.5: 2071–2100) from phase 5 of the Coupled Model Inter-comparison Project (CMIP5) are analyzed. Focusing on dynamically downscaled rainfall fields, the associated systematic biases originating from GCM and MRCM are removed based on observations using Parametric Quantile Mapping method in order to enhance the reliability of future projections. The MRCM simulations with bias correction capture the spatial patterns of seasonal rainfall as well as the frequency distribution of daily rainfall. Based on projected rainfall changes under both RCP4.5 and RCP8.5 scenarios, the ensemble of MRCM simulations project a significant decrease in rainfall over the western Maritime Continent during the inter-monsoon periods while the change in rainfall is not relevant during wet season. The main mechanism behind the simulated decrease in rainfall is rooted in asymmetries of the projected changes in seasonal dynamics of the meridional circulation along different latitudes. The sinking motion, which is marginally positioned in the reference simulation, is enhanced and expanded under global climate change, particularly in RCP8.5 scenario during boreal fall season. The projected enhancement of rainfall seasonality over the western Maritime Continent suggests increased risk of water stress for natural ecosystems as well as man-made water resources reservoirs.

Projection of Future Changes in Elephant Population in Amboseli under Representative Concentration Pathways

Within savanna environments, movements of elephant are influenced by changes in climate especially seasonal rainfall. In this study, we investigated the possible changes in elephant population based on projected rainfall changes using regional climate models (RCM) and Representative Concentration Pathways (RCPs). The relationship between elephant and rainfall was modelled against annual, wet season, dry season rainfall based on various time lags. Future relation between elephant and rainfall was projected based on three RCPs; 2.6, 4.5 and 8.5. There was a strong linear relationship between elephant and October-November-December (OND) rains with time lag of 13 years (Y = −4016.43 + 19.11x, r2 = 0.459, P = 0.006). The rainfall trends for RCP 2.6 and 4.5 showed a slight increase in annual rainfall for the period 2006-2100 but driven by OND increases. Rainfall increase for RCP 8.5 was significant and was driven by increase in both March-April-May (MAM) and OND. These rainfall dynamics had influence on the projected elephant population in the Amboseli ecosystem. For RCP 2.6 and 4.5 the elephant population increase was 2455 and 2814 respectively. RCP 8.5 elephant population doubled to an average of 3348 elephants. In all the RCPs there are seasonal and yearly variations and absolute number varies from the average. The range of variation is small in RCPs 2.6 and 4.5 compared to RCP 8.5. Evidently, elephant population will increase based on projected rainfall projections surpassing park capacity. It therefore, requires that the Park authority put in place measures that could contain these numbers including opening of blocked wildlife corridors, maintain the cross border movement of Amboseli elephant with Tanzania in that case ensure there is no poaching. Lastly, work with local communities so that they can benefit from tourism through setting up conservancies through which they could minimize the human elephant conflicts based on the projected elephant population.

Self-amplified Amazon forest loss due to vegetation-atmosphere feedbacks

Reduced rainfall increases the risk of forest dieback, while in return forest loss might intensify regional droughts. The consequences of this vegetation–atmosphere feedback for the stability of the Amazon forest are still unclear. Here we show that the risk of self-amplified Amazon forest loss increases nonlinearly with dry-season intensification. We apply a novel complex-network approach, in which Amazon forest patches are linked by observation-based atmospheric water fluxes. Our results suggest that the risk of self-amplified forest loss is reduced with increasing heterogeneity in the response of forest patches to reduced rainfall. Under dry-season Amazonian rainfall reductions, comparable to Last Glacial Maximum conditions, additional forest loss due to self-amplified effects occurs in 10–13% of the Amazon basin. Although our findings do not indicate that the projected rainfall changes for the end of the twenty-first century will lead to complete Amazon dieback, they suggest that frequent extreme drought events have the potential to destabilize large parts of the Amazon forest.

The impact of the Southern Annular Mode on future changes in Southern Hemisphere rainfall

AbstractA robust positive trend in the Southern Annular Mode (SAM) is projected for the end of the 21st century under the Representative Concentration Pathway 8.5 scenario, which results in rainfall decreases in the midlatitudes and increases in the high latitudes in the Southern Hemisphere (SH). We find that this SAM trend also increases rainfall over the SH subtropics in austral summer but not in winter, leading to a pronounced wintertime poleward expansion of the subtropical dry zone. These dynamically driven rainfall changes by the SAM appear to oppose the thermodynamically driven projected rainfall changes in the SH subtropics and midlatitudes, whereas the two components reinforce each other in the high latitudes. However, we show that most climate models fall short in capturing the observed SAM component driven by the El Niño–Southern Oscillation and associated rainfall in the austral warm seasons, which limits our confidence in quantifying the contribution of the SAM to projected rainfall changes.

Uncertainty in Tropical Rainfall Projections: Atmospheric Circulation Effect and the Ocean Coupling

Abstract Uncertainty in tropical rainfall projections under increasing radiative forcing is studied by using 26 models from phase 5 of the Coupled Model Intercomparison Project. Intermodel spread in projected rainfall change generally increases with interactive sea surface temperature (SST) warming in coupled models compared to atmospheric models with a common pattern of prescribed SST increase. Moisture budget analyses reveal that much of the model uncertainty in tropical rainfall projections originates from intermodel discrepancies in the dynamical contribution due to atmospheric circulation change. Intermodel singular value decomposition (SVD) analyses further show a tight coupling between the intermodel variations in SST warming pattern and circulation change in the tropics. In the zonal mean, the first SVD mode features an anomalous interhemispheric Hadley circulation, while the second mode displays an SST peak near the equator. The asymmetric mode is accompanied by a coupled pattern of wind–evaporation–SST feedback in the tropics and is further tied to interhemispheric asymmetric change in extratropical shortwave radiative flux at the top of the atmosphere. Intermodel variability in the tropical circulation change exerts a strong control on the spread in tropical cloud cover change and cloud radiative effects among models. The results indicate that understanding the coupling between the anthropogenic changes in SST pattern and atmospheric circulation holds the key to reducing uncertainties in projections of future changes in tropical rainfall and clouds.