Development of climate change projections for small watersheds using multi-model ensemble simulation and stochastic weather generation

Regional climate models (RCMs) have been increasingly used for climate change studies at the watershed scale. However, their performance is strongly dependent upon their driving conditions, internal parameterizations and domain configurations. Also, the spatial resolution of RCMs often exceeds the scales of small watersheds. This study developed a two-step downscaling method to generate climate change projections for small watersheds through combining a weighted multi-RCM ensemble and a stochastic weather generator. The ensemble was built on a set of five model performance metrics and generated regional patterns of climate change as monthly shift terms. The stochastic weather generator then incorporated these shift terms into observed climate normals and produced synthetic future weather series at the watershed scale. This method was applied to the Assiniboia area in southern Saskatchewan, Canada. The ensemble led to reduced biases in temperature and precipitation projections through properly emphasizing models with good performance. Projection of precipitation occurrence was particularly improved through introducing a weight-based probability threshold. The ensemble-derived climate change scenario was well reproduced as local daily weather series by the stochastic weather generator. The proposed combination of dynamical downscaling and statistical downscaling can improve the reliability and resolution of future climate projection for small prairie watersheds. It is also an efficient solution to produce alternative series of daily weather conditions that are important inputs for examining watershed responses to climate change and associated uncertainties.     

Improved confidence in climate change projections of precipitation evaluated using daily statistics from the PRUDENCE ensemble

An ensemble of regional climate modelling simulations from the European framework project PRUDENCE are compared across European sub-regions with observed daily precipitation from the European Climate Assessment dataset by characterising precipitation in terms of probability density functions (PDFs). Models that robustly describe the observations for the control period (1961–1990) in given regions as well as across regions are identified, based on the overlap of normalised PDFs, and then validated, using a method based on bootstrapping with replacement. We also compare the difference between the scenario period (2071–2100) and the control period precipitation using all available models. By using a metric quantifying the deviation over the entire PDF, we find a clearly marked increase in the contribution to the total precipitation from the more intensive events and a clearly marked decrease for days with light precipitation in the scenario period. This change is tested to be robust and found in all models and in all sub-regions. We find a detectable increase that scales with increased warming, making the increase in the PDF difference a relative indicator of climate change level. Furthermore, the crossover point separating decreasing from increasing contributions to the normalised precipitation spectrum when climate changes does not show any significant change which is in accordance with expectations assuming a simple analytical fit to the precipitation spectrum.     

Improved confidence in climate change projections of precipitation further evaluated using daily statistics from ENSEMBLES models

Probability density functions for daily precipitation data are used as a validation tool comparing station measurements to seven transient regional climate model runs, with a horizontal resolution of 25 km and driven by the SRES A1B scenario forcing, within the ENSEMBLES project. The validation is performed for the control period 1961–1990 for eight predefined European subregions, and a ninth region enclosing all eight subregions, with different climate characteristics. Models that best match the observations are then used for making climate change projections of precipitation distributions during the twenty-first century for each subregion separately. We find, compared to the control period, a distinct decrease in the contribution to the total precipitation for days with moderate precipitation and a distinct increase for days with more intense precipitation. This change in contribution to the total precipitation is found to amplify with time during all of the twenty-first century with an average rate of 1.1% K^?1. Furthermore, the crossover point separating the decreasing from the increasing contributions does not show any significant change with time for any specific subregion. These results are a confirmation and a specification of the results from a previous study using the same station measurements but with a regional climate model ensemble within the PRUDENCE project.     

Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.     

Present climate simulation over Korea with a regional climate model using a one-way double-nested system

Summary This study investigates the capability of the regional climate model RegCM3 to simulate surface air temperature and precipitation over the Korean Peninsula. The model is run in one-way double nested mode, with a 60 km grid point spacing “mother” domain encompassing the eastern regions of Asia and a 20 km grid point spacing nested domain covering the Korean Peninsula. The simulation spans the three-year period of 1 October 2000 through 30 September 2003 and the boundary conditions needed to run the mother domain experiment are provided from the NCEP reanalysis of observations. The model results are compared with a high density station observation dataset to examine the fine scale structure of the surface climate signal. The model shows a good performance in capturing both the sign and magnitude of the seasonal and inter-annual variations of the surface variables both over East Asia as a whole and over the Korean Peninsula in the nested system. Some persistent biases are however present. Surface temperature is systematically underestimated, especially over mountainous regions in the warm season. This feature may be due to the relatively coarse representation of the Korean topography. The simulated precipitation over the mother domain successfully reproduces the broad spatial pattern of observed precipitation over East Asia along with its seasonal evolution. On the other hand, fine scale details from the nested results show a varying level of quality for the different individual years. Because of the better resolved topographic forcing, the increased resolution of the nested model improves the spatial agreement with the fine scale observation fields for temperature and cold season precipitation. For summer monsoon precipitation the simulation of individual monsoon convective events and tropical storms is however more important than the topographic forcing, and therefore the performance of the nested system is more case-dependent.     

Improved bora wind simulation using a nested Eta Model

Summary In connection with a number of recent publications on anomalous (excessive) absorption of shortwave radiation (SWR) by clouds, the data of aircraft observations of spectral and total SWR vertical profiles in the troposphere obtained within the CAENEX, GAAREX and FGGE programmes have been discussed. These data demonstrated persuasively the existence of substantial SWR absorption by clouds in the visible wavelength region. In this context, the results of simulation numerical medelling of the SWR transfer in clouds have been considered. These show a significant enhancement of the SWR absorption by clouds due to an increase of the mean free path of photons under an impact of multiple scattering in clouds. Another important consideration may be the impact of SWR-absorbing pollutants in clouds, especially soot aerosols.With 4 Figures     

一个区域气候模式水文过程的改进及年尺度模拟研究

本文将更符合物理过程实际的考虑入渗非均匀和降水非均匀的水文模型VXM并入区域气候模式RegCM3模式,利用此区域水文气候模式分别对1988、1990、1991年3个不同气候年的水文气候进行了模拟.模拟结果表明,模式对入渗非均匀和降水非均匀的响应在年尺度上是敏感的:模式能成功模拟年平均降水及降水的年内变化,较好地再现了降水分布和大小;并入VXM模型后模式对南方径流的模拟能力得到较大的提高,模拟的年平均及年内变化与实际较为一致.结果还表明,径流机制的改进有助于改善降水模拟能力,并引起蒸发、温度等气候要素相应的变化;并入VXM模型后对模拟结果的影响更主要体现在夏季.     

Very high-resolution climate simulation over Fiji using a global variable-resolution model

A high-resolution climate model simulation has been performed for the first time for Fiji’s climatology. The simulation involved a numerical experiment for a 10-year period (1975–1984), and was conducted at a horizontal resolution of 8 km in a stretched-grid configuration, which is currently the highest resolution at which a global climate model has been applied for regional climatological simulations. Analysis of model-generated data demonstrates a fairly good skill of the CSIRO Conformal-Cubic Atmospheric Model (C-CAM) in the simulation of the annual cycles of maximum and minimum temperatures and rainfall at selected locations in Fiji. The model has also successfully reproduced the pattern of maximum and minimum surface air temperatures between the western and central divisions of Fiji. Model simulation of spatial and temporal distribution of monthly total rainfall (10-year mean) over the main island of Viti Levu in Fiji shows that it reproduces the observed intraseasonal and interannual variability; the influence of the El Niño phenomena has also been captured well in the model-simulated rainfall.     

The potential effects of climate change on malaria transmission in Africa using bias-corrected regionalised climate projections and a simple malaria seasonality model

Climatic conditions such as relatively cold temperatures and dryness are able to limit malaria transmission. Climate change is therefore expected to alter malaria spread. A previous assessment of the potential impacts of climate change on the seasonality of malaria in Africa is revisited. Bias-corrected regional climate projections with a horizontal resolution of 0.5° are used from the Regional Model (REMO), which include land use and land cover changes. The malaria model employed is the climate-driven seasonality model (MSM) from the Mapping Malaria Risk in Africa project for which a comparison with data from the Malaria Atlas Project (MAP) and the Liverpool Malaria Model (LMM), and a novel validation procedure lends more credence to results. For climate scenarios A1B and B1 and for 2001–2050, REMO projects an overall drying and warming trend in the African malaria belt, that is largely imposed by the man-made degradation of vegetation. As a result, the malaria projections of the MSM show a decreased length of the malaria season in West Africa. The northern Sahel is no more longer suitable for malaria in the projections and shorter malaria seasons are expected for various areas farther south. In East Africa, higher temperatures and nearly unchanged precipitation patterns lead to longer transmission seasons and an increase in highland malaria. Assuming constant population numbers, an overall increase in person-months of exposure of up to 6 % is found. The results of this simple seasonality model are similar to previous projections from the more complex LMM. However, a different response to the warming of highlands is found for the two models. It is concluded that the MSM is an efficient tool to assess the climate-driven malaria seasonality and that an uncertainty analysis of future malaria spread would benefit from a multi-model approach.     

Assessment of CMIP5 global model simulations and climate change projections for the 21 st century using a modified Thornthwaite climate classification

A modified Thornthwaite Climate Classification is applied to a 32-member ensemble of CMIP5 GCMs in order to 1) evaluate model performance in the historical climate and 2) assess projected climate change at the end of the 21 ^{s t} century following two greenhouse gas representative concentration pathways (RCP4.5 and RCP8.5). This classification scheme differs from the well-known Köppen approach as it uses potential evapotranspiration for thermal conditions, a moisture index for moisture conditions, and has even intervals between climate classes. The multi-model ensemble (MME) reproduces the main spatial features of the global climate reasonably well, however, in many regions the climate types are too moist. Extreme climate types, such as those found in polar and desert regions, as well as the cool- and cold-wet types of eastern North America and the warm and cool-moist types found in the southern U.S., eastern South America, central Africa and Europe are reproduced best by the MME. In contrast, the cold-dry and cold-semiarid climate types characterizing much of the high northern latitudes and the warm-wet type found in parts of Indonesia and southeast Asia are poorly represented by the MME. Regionally, most models exhibit the same sign in moisture and thermal biases, varying only in magnitude. Substantial changes in climate types are projected in both the RCP4.5 and RCP8.5 scenarios. Area coverage of torrid climate types expands by 11 % and 19 % in the RCP4.5 and RCP8.5 projections, respectively. Furthermore, a large portion of these areas in the tropics will experience thermal conditions which exceed the range of historical values and fall into a novel super torrid climate class. The greatest growth in moisture types in climate zones is among those with dry climates (moisture index values < 0) with increased areas of more than 8 % projected by the RCP8.5 MME.     

History matching for exploring and reducing climate model parameter space using observations and a large perturbed physics ensemble

We apply an established statistical methodology called history matching to constrain the parameter space of a coupled non-flux-adjusted climate model (the third Hadley Centre Climate Model; HadCM3) by using a 10,000-member perturbed physics ensemble and observational metrics. History matching uses emulators (fast statistical representations of climate models that include a measure of uncertainty in the prediction of climate model output) to rule out regions of the parameter space of the climate model that are inconsistent with physical observations given the relevant uncertainties. Our methods rule out about half of the parameter space of the climate model even though we only use a small number of historical observations. We explore 2 dimensional projections of the remaining space and observe a region whose shape mainly depends on parameters controlling cloud processes and one ocean mixing parameter. We find that global mean surface air temperature (SAT) is the dominant constraint of those used, and that the others provide little further constraint after matching to SAT. The Atlantic meridional overturning circulation (AMOC) has a non linear relationship with SAT and is not a good proxy for the meridional heat transport in the unconstrained parameter space, but these relationships are linear in our reduced space. We find that the transient response of the AMOC to idealised CO₂ forcing at 1 and 2 % per year shows a greater average reduction in strength in the constrained parameter space than in the unconstrained space. We test extended ranges of a number of parameters of HadCM3 and discover that no part of the extended ranges can by ruled out using any of our constraints. Constraining parameter space using easy to emulate observational metrics prior to analysis of more complex processes is an important and powerful tool. It can remove complex and irrelevant behaviour in unrealistic parts of parameter space, allowing the processes in question to be more easily studied or emulated, perhaps as a precursor to the application of further relevant constraints.     

Asian summer monsoon onset in simulations and CMIP5 projections using four Chinese climate models

The reproducibility and future changes of the onset of the Asian summer monsoon were analyzed based on the simulations and projections under the Representative Concentration Pathways(RCP) scenario in which anthropogenic emissions continue to rise throughout the 21 st century(i.e. RCP8.5) by all realizations from four Chinese models that participated in the Coupled Model Intercomparison Project Phase 5(CMIP5). Delayed onset of the monsoon over the Arabian Sea was evident in all simulations for present-day climate, which was associated with a too weak simulation of the low-level Somali jet in May.A consistent advanced onset of the monsoon was found only over the Arabian Sea in the projections, where the advanced onset of the monsoon was accompanied by an increase of rainfall and an anomalous anticyclone over the northern Indian Ocean. In all the models except FGOALS-g2, the enhanced low-level Somali jet transported more water vapor to the Arabian Sea, whereas in FGOALS-g2 the enhanced rainfall was determined more by the increased wind convergence. Furthermore,and again in all models except FGOALS-g2, the equatorial SST warming, with maximum increase over the eastern Pacific,enhanced convection in the central West Pacific and reduced convection over the eastern Indian Ocean and Maritime Continent region, which drove the anomalous anticyclonic circulation over the western Indian Ocean. In contrast, in FGOALS-g2, there was minimal(near-zero) warming of projected SST in the central equatorial Pacific, with decreased convection in the central West Pacific and enhanced convection over the Maritime Continent. The broader-scale differences among the models across the Pacific were related to both the differences in the projected SST pattern and in the present-day simulations.     

Vegetation response to climate and climatic extremes in northwest Bangladesh: a quantile regression approach

Theoretical and Applied Climatology - The present study assessed the vegetation response to climate in the water-stressed northwest Bangladesh (NWB). The quantile regression analysis was employed...     

The global impacts of US climate policy: a model simulation using GCAM-TU and MAGICC

To assess the potential impacts of the US withdrawal from the Paris Agreement, this study applied GCAM-TU (an updated version of the Global Change Assessment Model) to simulate global and regional emission pathways of energy-related CO₂, which show that US emissions in 2100 would reduce to ?2.4?Gt, ?0.7?Gt and ?0.2?Gt under scenarios of RCP2.6, RCP3.7 and RCP4.5, respectively. Two unfavourable policy scenarios were designed, assuming a temporary delay and a complete stop for US mitigation actions after 2015. Simulations by the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) indicate that the temperature increase by 2100 would rise by 0.081°C–0.161°C compared to the three original RCPs (Representative Concentration Pathways) if US emissions were kept at their 2015 levels until 2100. The probability of staying below 2°C would decrease by 6–9% even if the US resumes mitigation efforts for achieving its Nationally Determined Contribution (NDC) target after 2025. It is estimated by GCAM-TU that, without US participation, increased reduction efforts are required for the rest of the world, including developing countries, in order to achieve the 2°C goal, resulting in 18% higher global cumulative mitigation costs from 2015 to 2100.

Key policy insights

• President Trump’s climate policies, including planned withdrawal from the Paris Agreement, cast a shadow on international climate actions, and would lower the likelihood of achieving the 2°C target.

• To meet the 2°C target without the US means increased reduction efforts and mitigation costs for the rest of the world, and considerable economic burdens for major developing areas.

• Active state-, city- and enterprise-level powers should be supported to keep the emission reduction gap from further widening even with reduced mitigation efforts from the US federal government.

     

Climate-related uncertainties in projections of the twenty-first century terrestrial carbon budget: off-line model experiments using IPCC greenhouse-gas scenarios and AOGCM climate projections

A terrestrial ecosystem model (Sim-CYCLE) was driven by multiple climate projections to investigate uncertainties in predicting the interactions between global environmental change and the terrestrial carbon cycle. Sim-CYCLE has a spatial resolution of 0.5°, and mechanistically evaluates photosynthetic and respiratory CO₂ exchange. Six scenarios for atmospheric-CO₂ concentrations in the twenty-first century, proposed by the Intergovernmental Panel on Climate Change, were considered. For each scenario, climate projections by a coupled atmosphere–ocean general circulation model (AOGCM) were used to assess the uncertainty due to socio-economic predictions. Under a single CO₂ scenario, climate projections with seven AOGCMs were used to investigate the uncertainty stemming from uncertainty in the climate simulations. Increases in global photosynthesis and carbon storage differed considerably among scenarios, ranging from 23 to 37% and from 24 to 81 Pg C, respectively. Among the AOGCM projections, increases ranged from 26 to 33% and from 48 to 289 Pg C, respectively. There were regional heterogeneities in both climatic change and carbon budget response, and different carbon-cycle components often responded differently to a given environmental change. Photosynthetic CO₂ fixation was more sensitive to atmospheric CO₂, whereas soil carbon storage was more sensitive to temperature. Consequently, uncertainties in the CO₂ scenarios and climatic projections may create additional uncertainties in projecting atmospheric-CO₂ concentrations and climates through the interactive feedbacks between the atmosphere and the terrestrial ecosystem.     

Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 1: recent climate simulation (1971–2000)

We present an analysis of a high resolution multi-decadal simulation of recent climate (1971–2000) over the Korean Peninsula with a regional climate model (RegCM3) using a one-way double-nested system. Mean climate state as well as frequency and intensity of extreme climate events are investigated at various temporal and spatial scales, with focus on surface air temperature and precipitation. The mother intermediate resolution model domain encompasses the eastern regions of Asia at 60 km grid spacing while the high resolution nested domain covers the Korean Peninsula at 20 km grid spacing. The simulation spans the 30-year period of January 1971 through December 2000, and initial and lateral boundary conditions for the mother domain are provided from ECHO-G fields based on the IPCC SRES B2 scenario. The model shows a good performance in reproducing the climatological and regional characteristics of surface variables, although some persistent biases are present. Main results are as follows: (1) The RegCM3 successfully simulates the fine-scale structure of the temperature field due to topographic forcing but it shows a systematic cold bias mostly due to an underestimate of maximum temperature. (2) The frequency distribution of simulated daily mean temperature agrees well with the observed seasonal and spatial patterns. In the summer season, however, daily variability is underestimated. (3) The RegCM3 simulation adequately captures the seasonal evolution of precipitation associated to the East Asia monsoon. In particular, the simulated winter precipitation is remarkably good, clearly showing typical precipitation patterns that occur on the northwestern areas of Japan during the winter monsoon. Although summer precipitation is underestimated, area-averaged time series of precipitation over Korea show that the RegCM3 agrees better with observations than ECHO-G both in terms of seasonal evolution and precipitation amounts. (4) Heavy rainfall phenomena exceeding 300 mm/day are simulated only at the high resolution of the double nested domain. (5) The model shows a tendency to overestimate the number of precipitation days and to underestimate the precipitation intensities. (6) A CSEOF analysis reveals that the model captures the strength of the annual cycle and the surface warming trend throughout the simulated period.     

Clustering current climate regions of Turkey by using a multivariate statistical method

In this study, the hierarchical clustering technique, called Ward method, was applied for grouping common features of air temperature series, precipitation total and relative humidity series of 244 stations in Turkey. Results of clustering exhibited the impact of physical geographical features of Turkey, such as topography, orography, land–sea distribution and the high Anatolian peninsula on the geographical variability. Based on the monthly series of nine climatological observations recorded for the period of 1970–2010, 12 and 14 clusters of climate zones are determined. However, from the comparative analyses, it is decided that 14 clusters represent the climate of Turkey more realistically. These clusters are named as (1) Dry Summer Subtropical Semihumid Coastal Aegean Region; (2) Dry-Subhumid Mid-Western Anatolia Region; (3 and 4) Dry Summer Subtropical Humid Coastal Mediterranean region [(3) West coast Mediterranean and (4) Eastern Mediterranean sub-regions]; (5) Semihumid Eastern Marmara Transition Sub-region; (6) Dry Summer Subtropical Semihumid/Semiarid Continental Mediterranean region; (7) Semihumid Cold Continental Eastern Anatolia region; (8) Dry-subhumid/Semiarid Continental Central Anatolia Region; (9 and 10) Mid-latitude Humid Temperate Coastal Black Sea Region [(9) West Coast Black Sea and (10) East Coast Black Sea sub-regions]; (11) Semihumid Western Marmara Transition Sub-region; (12) Semihumid Continental Central to Eastern Anatolia Sub-region; (13) Rainy Summer Semihumid Cold Continental Northeastern Anatolia Sub-region; and (14) Semihumid Continental Mediterranean to Eastern Anatolia Transition Sub-region. We believe that this study can be considered as a reference for the other climate-related researches of Turkey, and can be useful for the detection of Turkish climate regions, which are obtained by a long-term time course dataset having many meteorological variables.     

Future projections of Indian Summer Monsoon under multiple RCPs using a high resolution global climate model multiforcing ensemble simulations

Climate Dynamics - Present-day simulations (1983–2003) of a global climate model of 60-km resolution with three deep convection schemes are analysed to find the best scheme for simulation of...