Climate Model Intercomparison Project Phase Research Articles

Projected major fire and vegetation changes in the Pacific Northwest of the conterminous United States under selected CMIP5 climate futures

Climate change adaptation and mitigation require understanding of vegetation response to climate change. Using the MC2 dynamic global vegetation model (DGVM) we simulate vegetation for the Northwest United States using results from 20 different Climate Model Intercomparison Project Phase 5 (CMIP5) models downscaled using the MACA algorithm. Results were generated for representative concentration pathways (RCPs) 4.5 and 8.5 under vegetation modeling scenarios with and without fire suppression for a total of 80 model runs for future projections. For analysis, results were aggregated by three subregions: the Western Northwest (WNW), from the crest of the Cascade Mountains west; Northwest Plains and Plateau (NWPP), the non-mountainous areas east of the Cascade Mountains; and Eastern Northwest Mountains (ENWM), the mountainous areas east of the Cascade Mountains. In the WNW, mean fire interval (MFI) averaged over all climate projections decreases by up to 48%, and potential vegetation shifts from conifer to mixed forest under RCP 4.5 and 8.5 with and without fire suppression. In the NWPP MFI averaged over all climate projections decreases by up to 82% without fire suppression and increases by up to 14% with fire suppression resulting in woodier vegetation cover. In the ENWM, MFI averaged across all climate projections decreases by up to 81%, subalpine communities are lost, but conifer forests continue to dominate the subregion in the future.

Using scaling for macroweather forecasting including the pause

AbstractThe ScaLIng Macroweather model (SLIMM) is a new class of stochastic atmospheric model. It exploits the large system memory to overcome the biases of conventional numerical climate models, it makes hindcasts and forecasts over macroweather forecast horizons (≈10 days to decades). Using the simplest (scalar), SLIMM model with only two parameters, we present various twentieth century hindcasts including several of the slowdown (“pause”) in the warming since 1998. The 1999–2013 hindcast is accurate to within ±0.11 K, with all the 2002–2013 anomalies hindcast to within ±0.02 K. In comparison, the Climate Model Intercomparison Project Phase 3 hindcasts were on average about 0.2 K too warm.

Impacts of global warming on residential heating and cooling degree-days in the United States.

Climate change is expected to decrease heating demand and increase cooling demand for buildings and affect outdoor thermal comfort. Here, we project changes in residential heating degree-days (HDD) and cooling degree-days (CDD) for the historical (1981–2010) and future (2080–2099) periods in the United States using median results from the Climate Model Intercomparison Project phase 5 (CMIP5) simulations under the Representation Concentration Pathway 8.5 (RCP8.5) scenario. We project future HDD and CDD values by adding CMIP5 projected changes to values based on historical observations of US climate. The sum HDD + CDD is an indicator of locations that are thermally comfortable, with low heating and cooling demand. By the end of the century, station median HDD + CDD will be reduced in the contiguous US, decreasing in the North and increasing in the South. Under the unmitigated RCP8.5 scenario, by the end of this century, in terms of HDD and CDD values considered separately, future New York, NY, is anticipated to become more like present Oklahoma City, OK; Denver, CO, becomes more like Raleigh, NC, and Seattle, WA, becomes more like San Jose, CA. These results serve as an indicator of projected climate change and can help inform decision-making.

The role of ENSO and PDO in variability of winter precipitation over North America from twenty first century CMIP5 projections

We investigate the combined impact of ENSO and PDO on North American winter climate in current and future climate projections from 11 global models in the Climate Model Intercomparison Project Phase 5 (CMIP5) dataset. We first analyze winter sea surface temperature, sea level pressure (SLP) and precipitation anomalies for the historical period 1951–2005, and find that the CMIP5 models reproduce well the constructive interference between ENSO and the PDO compared to observations (i.e. positive ENSO and PDO or negative ENSO and PDO). On the other hand, the destructive interference (positive ENSO and negative PDO or negative ENSO and positive PDO) is less accurately reproduced. Consistently with observations, ENSO events show generally more impact on North American winter climate than PDO events, although there is a robust increase of rainfall in the Southeastern US during the negative PDO phase. For the twenty first century projections, we focus on the 2050–2099 period under the RCP8.5 greenhouse gas concentration scenario and we find an overall strengthening of both the ENSO and PDO signals, and particularly the PDO one, on the SLP and related teleconnections. This results in an enhanced influence of the negative PDO phase on flood conditions in the Southeastern United States, and in drier conditions over the Southwest coasts of North America.

Climate change intensification of horizontal water vapor transport in CMIP5

AbstractGlobal warming of the Earth's atmosphere is hypothesized to lead to an intensification of the global water cycle. To determine associated hydrological changes, most previous research has used precipitation. This study, however, investigates projected changes to global atmospheric water vapor transport (integrated vapor transport (IVT)), the key link between water source and sink regions. Using 22 global circulation models from the Climate Model Intercomparison Project Phase 5, we evaluate, globally, the mean, standard deviation, and the 95th percentiles of IVT from the historical simulations (1979–2005) and two emissions scenarios (2073–2099). Considering the more extreme emissions, multimodel mean IVT increases by 30–40% in the North Pacific and North Atlantic storm tracks and in the equatorial Pacific Ocean trade winds. An acceleration of the high‐latitude IVT is also shown. Analysis of low‐altitude moisture and winds suggests that these changes are mainly due to higher atmospheric water vapor content.

The effect of increased fresh water from Antarctic ice shelves on future trends in Antarctic sea ice

AbstractObservations show that, in contrast to the Arctic, the area of Antarctic sea ice has increased since 1979. A potential driver of this significant increase relates to the mass loss of the Antarctic ice sheet. Subsurface ocean warming causes basal ice-shelf melt, freshening the surface waters around Antarctica, which leads to increases in sea-ice cover. With climate warming ongoing, future mass-loss rates are projected to accelerate, which has the potential to affect future Antarctic sea-ice trends. Here we investigate to what extent future sea-ice trends are influenced by projected increases in Antarctic freshwater flux due to subsurface melt, using a state-of-the-art global climate model (EC-Earth) in standardized Climate Model Intercomparison Project phase 5 (CMIP5) climate-change simulations. Virtually all CMIP5 models disregard ocean–ice-sheet interactions and project strongly retreating Antarctic sea ice. Applying various freshwater flux scenarios, we find that the additional fresh water significantly offsets the decline in sea-ice area and is even able to reverse the trend in the strongest freshwater forcing scenario that can reasonably be expected, especially in austral winter. The model also simulates decreasing sea surface temperatures (SSTs), with the SST trends exhibiting strong regional variations that largely correspond to regional sea-ice trends.

다양한 기후요소와 지표에 대한 CMIP5 GCMs 모델 성능 평가 -미국 남동부 지역을 대상으로-

본 연구에서는 전지구 기후모델의 성능을 평가함에 있어 기후 요소와 평가 지표에 따른 분석 결과의 다양성에 대해 살펴보고자 하였다. 미국 남동부 지역을 대상으로 17개의 CMIP5 GCM의 강우량, 일 최대 최저기온, 풍속에 대한 과거기간(1950~2000)의 모의 결과를 같은 기간의 관측치와 비교한 오차와 상관도를 이용하여 정량적으로 평가하였다. 기후 모델 산출물을 효과적으로 분석하기 위해 격자 단위 관측 자료를 평가기준으로 사용하였으며 다양한 형태의 기상 특성에 대한 모의 성능을 다각적으로 진단하기 위해 기후 정보(평균적 기후 통계량, 시간 변동성, 극한 사상 빈도 등)를 16개 지표로 정의하여 평가에 적용하였다. 또한 산정된 오차와 상관도를 기반으로 대상지역에 대한 기후요소별 GCM 성능 순위를 도출하여 비교하였다. 연구 결과, 기온에 대한 기후 특성에 대한 모델 재현성은 전반적으로 뛰어난 반면 강우량 및 풍속에 대한 모델 성능은 일 변동성을 제외한 대부분 지표들에 대해 비교적 낮은 것으로 나타났다. 더불어 모델의 정확도 순위는 기후 요소, 평가 지표, 그리고 오차 산정 방법에 따라 다양하게 나타남을 확인하였다. 특히 IPSL-CM5A-LR 모델은 대상지역에 대한 적용성이 현저히 낮은 것으로 나타났다. 본 연구는 다양한 기후변화 영향 연구에 적합한 모델 선정과 기후 모델의 불확실성을 고려한 합리적 미래 예측을 위해서는 다각적이고 면밀한 모델 평가가 선행되어야 함을 시사한다. The goal of this study is to demonstrate the diversity of model performance for various climatic elements and indicators. We evaluated the skills of the most advanced 17 General Circulation Models (GCMs) i.e., CMIP5 (Climate Model Inter-comparison project, phase 5) climate models in reproducing retrospective climatology from 1950 to 2000 over the Southeast US for the key climatic elements important in the hydrological and agricultural perspectives (i.e., precipitation, maximum and minimum temperature, and wind speed). The biases of raw CMIP5 GCMs were estimated for 16 different climatic indicators that imply mean climatology, temporal variability, extreme frequency, etc. using a grid-based observational dataset as reference. Based on the error (RMSE) and correlation (R) of GCM outputs, the error-based GCM ranks were assigned on average over the indicators. Overall, the GCMs showed much better accuracy in representing mean climatology of temperature comparing to other elements whereas few GCM showed acceptable skills for precipitation. It was also found that the model skills and ranks would be substantially different by the climatic elements, error statistics applied for evaluation, and indicators as well. This study presents significance of GCM uncertainty and the needs of considering rational strategies for climate model evaluation and selection.

Long‐term changes in lower tropospheric baseline ozone concentrations: Comparing chemistry‐climate models and observations at northern midlatitudes

AbstractTwo recent papers have quantified long‐term ozone (O3) changes observed at northern midlatitude sites that are believed to represent baseline (here understood as representative of continental to hemispheric scales) conditions. Three chemistry‐climate models (NCAR CAM‐chem, GFDL‐CM3, and GISS‐E2‐R) have calculated retrospective tropospheric O3 concentrations as part of the Atmospheric Chemistry and Climate Model Intercomparison Project and Coupled Model Intercomparison Project Phase 5 model intercomparisons. We present an approach for quantitative comparisons of model results with measurements for seasonally averaged O3 concentrations. There is considerable qualitative agreement between the measurements and the models, but there are also substantial and consistent quantitative disagreements. Most notably, models (1) overestimate absolute O3 mixing ratios, on average by ~5 to 17 ppbv in the year 2000, (2) capture only ~50% of O3 changes observed over the past five to six decades, and little of observed seasonal differences, and (3) capture ~25 to 45% of the rate of change of the long‐term changes. These disagreements are significant enough to indicate that only limited confidence can be placed on estimates of present‐day radiative forcing of tropospheric O3 derived from modeled historic concentration changes and on predicted future O3 concentrations. Evidently our understanding of tropospheric O3, or the incorporation of chemistry and transport processes into current chemical climate models, is incomplete. Modeled O3 trends approximately parallel estimated trends in anthropogenic emissions of NOx, an important O3 precursor, while measured O3 changes increase more rapidly than these emission estimates.

An evaluation of the CMIP3 and CMIP5 simulations in their skill of simulating the spatial structure of SST variability

The natural sea surface temperature (SST) variability in the global oceans is evaluated in simulations of the Climate Model Intercomparison Project Phase 3 (CMIP3) and CMIP5 models. In this evaluation, we examine how well the spatial structure of the SST variability matches between the observations and simulations on the basis of their leading empirical orthogonal functions-modes. Here we focus on the high-pass filter monthly mean time scales and the longer 5 years running mean time scales. We will compare the models and observations against simple null hypotheses, such as isotropic diffusion (red noise) or a slab ocean model, to illustrate the models skill in simulating realistic patterns of variability. Some models show good skill in simulating the observed spatial structure of the SST variability in the tropical domains and less so in the extra-tropical domains. However, most models show substantial deviations from the observations and from each other in most domains and particularly in the North Atlantic and Southern Ocean on the longer (5 years running mean) time scale. In many cases the simple spatial red noise null hypothesis is closer to the observed structure than most models, despite the fact that the observed SST variability shows significant deviations from this simple spatial red noise null hypothesis. The CMIP models tend to largely overestimate the effective spatial number degrees of freedom and simulate too strongly localized patterns of SST variability at the wrong locations with structures that are different from the observed. However, the CMIP5 ensemble shows some improvement over the CMIP3 ensemble, mostly in the tropical domains. Further, the spatial structure of the SST modes of the CMIP3 and CMIP5 super ensemble is more realistic than any single model, if the relative explained variances of these modes are scaled by the observed eigenvalues.

Changes in Surface Wind Speed over North America from CMIP5 Model Projections and Implications for Wind Energy

The centennial trends in the surface wind speed over North America are deduced from global climate model simulations in the Climate Model Intercomparison Project—Phase 5 (CMIP5) archive. Using the 21st century simulations under the RCP 8.5 scenario of greenhouse gas emissions, 5–10 percent increases per century in the 10 m wind speed are found over Central and East-Central United States, the Californian Coast, and the South and East Coasts of the USA in winter. In summer, climate models projected decreases in the wind speed ranging from 5 to 10 percent per century over the same coastal regions. These projected changes in the surface wind speed are moderate and imply that the current estimate of wind power potential for North America based on present-day climatology will not be significantly changed by the greenhouse gas forcing in the coming decades.

Blunt ocean dynamical thermostat in response of tropical eastern Pacific SST to global warming

Using an intermediate ocean–atmosphere coupled model (ICM) for the tropical Pacific, we investigated the role of the ocean dynamical thermostat (ODT) in regulating the tropical eastern Pacific sea surface temperature (SST) under global warming conditions. The external, uniformly distributed surface heating results in the cooling of the tropical eastern Pacific “cold tongue,” and the amplitude of the cooling increases as more heat is added but not simply linearly. Furthermore, an upper bound for the influence of the equatorially symmetric surface heating on the cold tongue cooling exists. The additional heating beyond the upper bound does not cool the cold tongue in a systematic manner. The heat budget analysis suggests that the zonal advection is the primary factor that contributes to such nonlinear SST response. The radiative heating due to the greenhouse effect (hereafter, RHG) that is obtained from the multi-model ensemble of the Climate Model Intercomparison Project Phase III (CMIP3) was externally given to ICM. The RHG obtained from the twentieth century simulation intensified the cold tongue cooling and the subtropical warming, which were further intensified by the RHG from the doubled CO2 concentration simulation. However, the cold tongue cooling was significantly reduced and the negative SST response region was shrunken toward the equator by the RHG from the quadrupled CO2 concentration simulation, while the subtropical warming increased further. A systematic RHG forced experiment having the same spatial pattern of RHG from doubled CO2 concentration simulation with different amplitude of forcing revealed that the ocean dynamical response to global warming tended to enhance the cooling in the tropical eastern Pacific by virtue of meridional advection and upwelling; however, these cooling effects could not fully compensate a given RHG warming as the external forcing becomes larger. Moreover, the feedback by the zonal thermal advection actually exerted the warming over the equatorial region. Therefore, as the global warming is intensified, the cooling over the eastern tropical Pacific by ODT and the negative SST response area are reduced.

The global impact of the transport sectors on atmospheric aerosol: simulations for year 2000 emissions

Abstract. We use the EMAC (ECHAM/MESSy Atmospheric Chemistry) global model with the aerosol module MADE (Modal Aerosol Dynamics model for Europe, adapted for global applications) to quantify the impact of transport emissions (land transport, shipping and aviation) on the global aerosol. We consider a present-day (2000) scenario according to the CMIP5 (Climate Model Intercomparison Project Phase 5) emission data set developed in support of the IPCC (Intergovernmental Panel on Climate Change) Fifth Assessment Report. The model takes into account particle mass and number emissions: The latter are derived from mass emissions under different assumptions on the size distribution of particles emitted by the three transport sectors. Additional sensitivity experiments are performed to quantify the effects of the uncertainties behind such assumptions. The model simulations show that the impact of the transport sectors closely matches the emission patterns. Land transport is the most important source of black carbon (BC) pollution in the USA, Europe and the Arabian Peninsula, contributing up to 60–70% of the total surface-level BC concentration in these regions. Shipping contributes about 40–60% of the total aerosol sulfate surface-level concentration along the most-traveled routes of the northern Atlantic and northern Pacific oceans, with a significant impact (~ 10–20%) along the coastlines. Aviation mostly affects aerosol number, contributing about 30–40% of the particle number concentration in the northern midlatitudes' upper troposphere (7–12 km), although significant effects are also simulated at the ground, due to the emissions from landing and take-off cycles. The transport-induced perturbations to the particle number concentrations are very sensitive to the assumptions on the size distribution of emitted particles, with the largest uncertainties (about one order of magnitude) obtained for the land transport sector. The simulated climate impacts, due to aerosol direct and indirect effects, are strongest for the shipping sector, in the range of −222.0 to −153.3 mW m−2, as a consequence of the large impact of sulfate aerosol on low marine clouds and their optical properties.

Hydrologic impacts of future climate change on Southeast US watersheds

The hydrological impact of climate change is assessed for 28 watersheds located within the Southeast United States using output from global climate models (GCMs) from the Climate Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) run. Subsequently, the impact of projected change in seasonal streamflow is derived by propagating projected scenarios, generated using changes derived from GCMs and weather generators, through a suite of conceptual hydrological models. Analysis shows that the spread in the magnitude of change in temperature and rainfall for CMIP3 is wider than that for CMIP5. The reduction in the spread among many factors may be attributed to improved physics, model number and resolution, and emission scenarios. The spread in projected change in temperature (precipitation) increases (decreases) from southernmost to northernmost latitude. Hydrological projection with CMIP3 output for the 2070s shows that streamflow decreases for most of the watersheds in spring and summer and increased in fall. In contrast, CMIP5 results show an increase in flow for all seasons except with the high-end scenarios in spring. However, the uncertainty in projections in streamflow is high with model uncertainty dominating emission scenario. The variability in prediction uncertainty among watersheds is partly explained by the variability in wetness index. The probability distribution function for projected seasonal flow for each scenario is markedly wide and therefore reflects that the uncertainty associated with using multiple GCMs from both CMIP3 and CMIP5 experiment is high which makes design and implementation of adaption measure a difficult task.

Evaluation of ACCESS climate model ocean diagnostics in CMIP5 simulations

Global and regional diagnostics are used to evaluate the ocean performance of the Australian Community Climate and Earth System Simulator coupled model (ACCESS-CM) contributions to the Climate Model Intercomparison Project phase 5 (CMIP5). Two versions of ACCESS-CM have been submitted to CMIP; namely CSIRO-BOM ACCESS1.0 and CSIRO-BOM ACCESS1.3. Results from six of the core CMIP5 experiments (piControl, historical, rcp45, rcp85, 1pctCO2, and abrupt4xCO2) are evaluated for each of the two ACCESS-CM model versions. Overall, both model versions exhibit a reasonable and stable representation of key diagnostics of ocean climate performance in the pre-industrial control simulations, including a meridional overturning circulation with North Atlantic Deep Water maxima in the range 22–24 Sv, and a poleward heat transport maximum of around 1.5 PW. For the projected climate change scenarios considered the ACCESS-CM results are in reasonable agreement with responses found in other CMIP models, with the familiar ocean warming, and reduction in strength of meridional overturning and poleward heat transport. Drifts in the control simulations of both global ocean salinity and global sea-level are opposite in sign for ACCESS1.0 and ACCESS1.3, suggesting problems exist in the closure of the hydrological cycle. The simulation of ocean climate change over the historical period shows a weak response compared to observations, which manifests as a late response of ocean warming and sea level rise starting around 1990 in the model, compared to the mid 1960s in observations. Further historical simulations are underway to ascertain if this late response in ACCESS is a robust model feature, or just low frequency variability. If the weak response over the historical period proves robust, the likely cause is a too strong cooling from atmospheric aerosols. Broadening the set of experiments to further investigate the relative warming response of the ACCESS-CM to greenhouse gases compared to the cooling response to aerosols is underway, and preliminary results do suggest that the cooling due to aerosols is strong in the historical simulations.

Arctic sea ice reduction and European cold winters in CMIP5 climate change experiments

European winter climate and its possible relationship with the Arctic sea ice reduction in the recent past and future as simulated by the models of the Climate Model Intercomparison Project phase 5 (CMIP5) is investigated, with focus on the cold winters. While Europe will warm overall in the future, we find that episodes of cold months will continue to occur and there remains substantial probability for the occurrence of cold winters in Europe linked with sea ice reduction in the Barents and Kara Sea sector. A pattern of cold‐European warm‐Arctic anomaly is typical for the cold events in the future, which is associated with the negative phase of the Arctic Oscillation. These patterns, however, differ from the corresponding patterns in the historical period, and underline the connection between European cold winter events and Arctic sea ice reduction.

Quality assessment concept of the World Data Center for Climate and its application to CMIP5 data

Abstract. The preservation of data in a high state of quality which is suitable for interdisciplinary use is one of the most pressing and challenging current issues in long-term archiving. For high volume data such as climate model data, the data and data replica are no longer stored centrally but distributed over several local data repositories, e.g. the data of the Climate Model Intercomparison Project Phase 5 (CMIP5). The most important part of the data is to be archived, assigned a DOI, and published according to the World Data Center for Climate's (WDCC) application of the DataCite regulations. The integrated part of WDCC's data publication process, the data quality assessment, was adapted to the requirements of a federated data infrastructure. A concept of a distributed and federated quality assessment procedure was developed, in which the workload and responsibility for quality control is shared between the three primary CMIP5 data centers: Program for Climate Model Diagnosis and Intercomparison (PCMDI), British Atmospheric Data Centre (BADC), and WDCC. This distributed quality control concept, its pilot implementation for CMIP5, and first experiences are presented. The distributed quality control approach is capable of identifying data inconsistencies and to make quality results immediately available for data creators, data users and data infrastructure managers. Continuous publication of new data versions and slow data replication prevents the quality control from check completion. This together with ongoing developments of the data and metadata infrastructure requires adaptations in code and concept of the distributed quality control approach.

Quantitative assessment of the climate components driving the pacific decadal oscillation in climate models

The Pacific decadal oscillation (PDO) is defined as the first empirical orthogonal function (EOF) mode of the North Pacific sea surface temperature anomalies. In this study, we reconstructed the PDO using the first-order autoregressive model from various climate indices representing the El Nino-Southern oscillation (ENSO), Aleutian Low (AL), sea surface height (SSH), and thermocline depth over the Kuroshio–Oyashio extension (KOE) region. The climate indices were obtained from observation and twentieth-century simulations of the eight coupled general circulation models (CGCMs) participating in the Climate Model Intercomparison Project Phase III (CMIP3). In this manner, we quantitatively assessed the major climate components generating the PDO using observation and models. Based on observations, the PDO pattern in the central to eastern North Pacific was accurately reconstructed by the AL and ENSO indices, and that in the western North Pacific was best reconstructed by the SSH and thermocline indices. In the CMIP3 CGCMs, the relative contribution of each component to the generation of the PDO varied greatly from model to model, and observations, although the PDO patterns from most of the models were similar to the pattern observed. In the models, the PDO pattern in the eastern and western North Pacific were well reconstructed using the AL and SSH indices, respectively. However, the PDO pattern reconstructed by the ENSO index was quite different from the observed pattern, which was possibly due to the model's common deficiency in simulating the amplitude and location of the ENSO. Furthermore, the differences in the contribution of the KOE thermocline index between the observed pattern and most of the models indicated that the PDO pattern associated with ocean wave dynamics is not properly simulated by most models. Therefore, the virtually well simulated PDO pattern by models is a result of physically inconsistent processes.

21st century Wisconsin snow projections based on an operational snow model driven by statistically downscaled climate data

AbstractOutput from the Climate Model Intercomparison Project Phase 3 (CMIP3) global climate models are statistically downscaled across Wisconsin, using a method that restores the observed mean, variance, and extremes of daily temperature and precipitation. The downscaled climate data for the late 20th century, mid‐21st century, and late 21st‐century is used to drive the National Weather Service operational snow model, SNOW‐17, to produce high‐resolution (0.1° × 0.1°) projections of daily snowfall, snow depth, and snow cover for Wisconsin. These snow projections will guide wildlife scientists in climate change impact studies and the development of adaptation strategies for the state, in addition to being of value to hydrologists, agricultural scientists, and other experts. SNOW‐17 simulations suggest a dramatic shortening of the Wisconsin snow season, with the greatest snowfall and snow depth reductions in spring, particularly over northern Wisconsin. Snowfall is substantially reduced in response to projected warming and only slightly offset by a projected increase in cold‐season precipitation. Percent reductions in snow depth are likely to be even more impressive than in snowfall, given not only a reduced frequency that falling precipitation will be in frozen form but also an enhanced snowmelt due to rising temperatures. Copyright © 2010 Royal Meteorological Society