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NASA NTRS1994

NCAR CCM2 simulation of the modern Antarctic climate

The National Center for Atmospheric Research (NCAR) community climate model version 2 (CCM2) simulation of the circumpolar trough, surface air temperature, the polar vortex, cloudiness, winds, and atmospheric moisture and energy budgets are examined to validate the model's representation of the present-day Antarctic climate. The results show that the CCM2 can well simulate many important climate features over Antarctica, such as the location and intensity of the circumpolar trough, the coreless winter over the plateau, the intensity and horizontal distribution of the surface inversion, the speed and streamline pattern of the katabatic winds, the double jet stream feature over the southern Indian and Pacific oceans, and the arid climate over the continent. However, there are also some serious errors in the model. Some are due to old problems but some are caused by the new parameterizations in the model. The model errors over high southern latitudes can be summarized as follows: The circumpolar trough, the polar vertex, and the westerlies in midlatitudes are too strong; the semiannual cycle of the circumpolar trough is distorted compared to the observations; the low centers of the circumpolar trough and the troughs in the middle and upper troposphere are shifted eastward by 15 deg - 40 deg longitude; the surface temperatures are too cold over the plateau in summer and over the coastline in winter; the polar tropopause continues to have a cold bias; and the cloudiness is too high over the continent. These biases are induced by two major factors: (1) the cloud optical properties in tropical and middle latitudes, which cause the eastward shift of troughs and surface low centers and the error in the semiannual cycle, and (2) the cold bias of the surface air temperature, which is attributed to the oversimulation of cloudiness over the continent, especially during summer, and the uniform 2-m-thick sea ice. The constant thickness of sea ice suppresses the energy flux from the ocean to the atmosphere and hence reduces the air temperature near the coast during winter. Finally, although the simulated Antarctic climate still suffers these biases, the overall performance of the CCM2 is much better than that of the CCM1-T42. Therefore the CCM2 is good enough to be used for climate change studies, especially over Antarctica.

Tzeng, Ren-Yow↗

NASA NTRS2018

Distinct Influences of Land Cover and Land Management on Seasonal Climate

Anthropogenic land use and land cover change is primarily represented in climate model simulations through prescribed transitions from natural vegetation to cropland or pasture. However, recent studies have demonstrated that land management practices, especially irrigation, have distinct climate impacts. Here we disentangle the seasonal climate impacts of land cover change and irrigation across areas of high agricultural intensity using climate simulations with three different land surface scenarios: (1) natural vegetation cover/no irrigation, (2) year 2000 crop cover/no irrigation, and (3) year 2000 crop cover and irrigation rates. We find that irrigation substantially amplifies land cover‐induced climate impacts but has opposing effects across certain regions. Irrigation mostly causes surface cooling, which substantially amplifies land cover change‐induced cooling in most regions except over Central, West, and South Asia, where it reverses land cover change‐induced warming. Despite increases in net surface radiation in some regions, this cooling is associated with enhancement of latent relative to sensible heat fluxes by irrigation. Similarly, irrigation substantially enhances the wetting influence of land cover change over several regions including West Asia and the Mediterranean. The most notable contrasting impacts of these forcings on precipitation occur over South Asia, where irrigation offsets the wetting influence of land cover during the monsoon season. Differential changes in regional circulations and moist static energy induced by these forcings contribute to their precipitation impacts and are associated with differential changes in surface and tropospheric temperature gradients and moisture availability. These results emphasize the importance of including irrigation forcing to evaluate the combined impacts of land surface changes for attributing historical climatic changes and managing future impacts.

Singh, Deepti↗

NASA NTRS2023

Importance of Internal Variability for Climate Model Assessment

Benchmarking climate model simulations against observations of the climate is core to the process of building realistic climate models and developing accurate future projections. However, in many cases, models do not match historical observations, particularly on regional scales. If there is a mismatch between modeled and observed climate features, should we necessarily conclude that our models are deficient? Using several illustrative examples, we emphasize that internal variability can easily lead to marked differences between the basic features of the model and observed climate, even when decades of model and observed data are available. This can appear as an apparent failure of models to capture regional trends or changes in global teleconnections, or simulation of extreme events. Despite a large body of literature on the impact of internal variability on climate, this acknowledgment has not yet penetrated many model evaluation activities, particularly for regional climate. We emphasize that using a single or small ensemble of simulations to conclude that a climate model is in error can lead to premature conclusions on model fidelity. A large ensemble of multidecadal simulations is therefore needed to properly sample internal climate variability in order to robustly identify model deficiencies and convincingly demonstrate progress between generations of climate models.

Climate and Earth system modelling↗

NASA NTRS2002

Mesoscale Convective Systems During SCSMEX: Simulations with a Regional Climate Model and a Cloud-Resolving Model

The South China Sea Monsoon Experiment (SCSMEX) was conducted in May-June 1998. One of its major objectives is to better understand the key physical processes for the onset and evolution of the summer monsoon over Southeast Asia and southern China. Multiple observation platforms (e.g., upper-air soundings, Doppler radar, ships, wind profilers, radiometers, etc.) during SCSMEX provided a first attempt at investigating the detailed characteristics of convection and circulation changes associated with monsoons over the South China Sea region. SCSMEX also provided precipitation derived from atmospheric budgets and comparison to those obtained from the Tropical Rainfall Measuring Mission (TRMM). In this paper, a regional scale model (with grid size of 20 km) and Goddard Cumulus Ensemble (GCE) model (with 1 km grid size) are used to perform multi-day integration to understand the precipitation processes associated with the summer monsoon over Southeast Asia and southern China. The regional climate model is used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during SCSMEX Sensitivity tests on various land surface models, sea surface temperature (SST) variations, and cloud processes are performed to understand the precipitation processes associated with the onset of the monsoon over the S. China Sea during SCSMEX. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. Cloud processes can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. The GCE-model results captured many observed precipitation characteristics because it used a fine grid size. For example, the model simulated rainfall temporal variation compared quite well to the sounding-estimated rainfall. The results show there are more latent heat fluxes prior to the onset of the monsoon. However, more rainfall was simulated after the onset of the monsoon. This modeling study indicates the latent heat fluxes (or evaporation) have more of an impact on precipitation processes and rainfall in the regional climate model simulations than in the cloud-resolving model simulations. Research is underway to determine if the difference in the grid sizes or the moist processes used in these two models is responsible for the differing influence of surface fluxes an precipitation processes.

Tao, W.-K.↗

NASA NTRS1991

Climate dynamics experiments using a GCM simulations

The study of surface-atmosphere interactions has begun with studies of the effect of altering the ocean and land boundaries. A ten year simulation of global climate using observed sea surface temperature anomalies has begun using the NCAR Community Climate Model (CCM1). The results for low resolution (R15) were computed for the first 8 years of the simulation and compared with the observed surface temperatures and the MSU (Microwave Sounding Unit) observations of tropospheric temperature. A simulation at higher resolution (T42) was done to ascertain the effect of interactive soil hydrology on the system response to an El Nino sea surface temperature perturbation. Initial analysis of this simulations was completed.

Fitzjarrald, Dan↗

NASA NTRS1990

The sensitivity of terrestrial carbon storage to climate change

The role of the terrestrial biosphere in controlling atmospheric CO2 levels during climate perturbations is estimated. Simulations are used to calculate the local geographical distribution of vegetation during the last glacial maximum. The known changes in sea level at this time, together with the simulated climate-driven spatial arrangement of vegetation, result in a mass transfer of carbon from the terrestrial biosphere to the atmosphere ranging from 30 Gt (corresponding to 15 ppm CO2) to -50 Gt (25 ppm). Thus, although the biosphere may have contributed to the decrease in atmospheric CO2 at 80 ppm, known to have occurred at 18 kyr, it does not seem to have been a dominant factor. For simulations run with twice the present-day CO2 levels, strong negative feedbacks appear which remove 235 Gt of carbon from the atmosphere.

Prentice, Katharine C.↗

NASA NTRS1982

The radiative impact of cumulus cloudiness in a general circulation model

The effect of cumulus cloudiness on the radiational heating and, on other aspects of the climate were simulated by the GLAS Climate Model. An experiment in which the cumulus cloudiness is neglected completely for purposes of the solar and terrestrial radiation parameterizations was performed. The results are compared with those of a control run, in which 100% cumulus cloud cover is assumed. The net solar radiation input into the Earth atmosphere system is more realistic in the experiment, and the model's underprediction of the global mean outgoing thermal radiation at the top of the atmosphere is reduced. The results suggest that there is a positive feedback between cumulus convection and the radiation field. The upper troposphere is warmer in the experiment, the surface air temperature increases over land, and the thermal lows over the continents intensity.

Moeng, C. H.↗

NASA NTRS2021

A data–model approach to interpreting speleothem oxygen isotope records from monsoon regions

Reconstruction of past changes in monsoon climate from speleothem oxygen isotope (δ 18 O) records is complex because δ 18 O signals can be influenced by multiple factors including changes in precipitation, precipitation recycling over land, temperature at the moisture source, and changes in the moisture source region and transport pathway. Here, we analyse >150 speleothem records of the Speleothem Isotopes Synthesis and AnaLysis (SISAL) database to produce composite regional trends in δ 18 O in monsoon regions; compositing minimises the influence of site-specific karst and cave processes that can influence individual site records. We compare speleothem δ 18 O observations with isotope-enabled climate model simulations to investigate the specific climatic factors causing these regional trends. We focus on differences in δ 18 O signals between the mid-Holocene, the peak of the Last Interglacial (Marine Isotope Stage 5e) and the Last Glacial Maximum as well as on δ 18 O evolution through the Holocene. Differences in speleothem δ 18 O between the mid-Holocene and the Last Interglacial in the East Asian and Indian monsoons are small, despite the larger summer insolation values during the Last Interglacial. Last Glacial Maximum δ 18 O values are significantly less negative than interglacial values. Comparison with simulated glacial–interglacial δ 18 O shows that changes are principally driven by global shifts in temperature and regional precipitation. Holocene speleothem δ 18 O records show distinct and coherent regional trends. Trends are similar to summer insolation in India, China and southwestern South America, but they are different in the Indonesian–Australian region. Redundancy analysis shows that 37 % of Holocene variability can be accounted for by latitude and longitude, supporting the differentiation of records into individual monsoon regions. Regression analysis of simulated precipitation δ 18 O and climate variables show significant relationships between global Holocene monsoon δ 18 O trends and changes in precipitation, atmospheric circulation and (to a lesser extent) source area temperature, whereas precipitation recycling is non-significant. However, there are differences in regional-scale mechanisms: there are clear relationships between changes in precipitation and δ 18 O for India, southwestern South America and the Indonesian–Australian regions but not for the East Asian monsoon. Changes in atmospheric circulation contribute to δ 18 O trends in the East Asian, Indian and Indonesian–Australian monsoons, and a weak source area temperature effect is observed over southern and central America and Asia. Precipitation recycling is influential in southwestern South America and southern Africa. Overall, our analyses show that it is possible to differentiate the impacts of specific climatic mechanisms influencing precipitation δ 18 O and use this analysis to interpret changes in speleothem δ 18 O.

speleothem oxygen isotope records↗

NASA NTRS2022

The Ozone–Climate Penalty Over South America and Africa By 2100

Climate change has the potential to increase surface ozone (O3) concentrations, known as the “ozone–climate penalty”, through changes to atmospheric chemistry, transport and dry deposition. In the tropics, the response of surface O3 to changing climate is relatively understudied but has important consequences for air pollution and human and ecosystem health. In this study, we evaluate the change in surface O3 due to climate change over South America and Africa using three state-of-the-art Earth system models that follow the Shared Socioeconomic Pathway 3-7.0 emission scenario from CMIP6. In order to quantify changes due to climate change alone, we evaluate the difference between simulations including climate change and simulations with a fixed present-day climate. We find that by 2100, models predict an ozone–climate penalty in areas where O3 is already predicted to be high due to the impacts of precursor emissions, namely urban and biomass burning areas, although on average, models predict a decrease in surface O3 due to climate change. We identify a small but robust positive trend in annual mean surface O3 over polluted areas. Additionally, during biomass burning seasons, seasonal mean O3 concentrations increase by 15 ppb (model range 12 to 18 ppb) in areas with substantial biomass burning such as the arc of deforestation in the Amazon. The ozone–climate penalty in polluted areas is shown to be driven by an increased rate of O3 chemical production, which is strongly influenced by NOx concentrations and is therefore specific to the emission pathway chosen. Multiple linear regression finds the change in NOx concentration to be a strong predictor of the change in O3 production, whereas increased isoprene emission rate is positively correlated with increased O3 destruction, suggesting NOx-limited conditions over the majority of tropical Africa and South America. However, models disagree on the role of climate change in remote, low-NOx regions, partly because of significant differences in NOx concentrations produced by each model. We also find that the magnitude and location of the ozone–climate penalty in the Congo Basin has greater inter-model variation than that in the Amazon, so further model development and validation are needed to constrain the response in central Africa. We conclude that if the climate were to change according to the emission scenario used here, models predict that forested areas in biomass burning locations and urban populations will be at increasing risk of high O3 exposure, irrespective of any direct impacts on O3 via the prescribed emission scenario.

Surface ozone↗

NASA NTRS2017

The DeepMIP Contribution to PMIP4: Experimental Design for Model Simulations of the EECO, PETM, and pre-PETM (version 1.0)

Past warm periods provide an opportunity to evaluate climate models under extreme forcing scenarios, in particular high ( greater than 800 ppmv) atmospheric CO2 concentrations. Although a post hoc intercomparison of Eocene (approximately 50 Ma) climate model simulations and geological data has been carried out previously, models of past high-CO2 periods have never been evaluated in a consistent framework. Here, we present an experimental design for climate model simulations of three warm periods within the early Eocene and the latest Paleocene (the EECO, PETM, and pre-PETM). Together with the CMIP6 pre-industrial control and abrupt 4(times) CO2 simulations, and additional sensitivity studies, these form the first phase of DeepMIP - the Deep-time Model Intercomparison Project, itself a group within the wider Paleoclimate Modeling Intercomparison Project (PMIP). The experimental design specifies and provides guidance on boundary conditions associated with palaeogeography, greenhouse gases, astronomical configuration, solar constant, land surface processes, and aerosols. Initial conditions, simulation length, and output variables are also specified. Finally, we explain how the geological data sets, which will be used to evaluate the simulations, will be developed.

climate models↗

NASA NTRS1988

Equatorial waves simulated by the NCAR community climate model

The equatorial planetary waves simulated by the NCAR CCM1 general circulation model were investigated in terms of space-time spectral analysis (Kao, 1968; Hayashi, 1971, 1973) and energetic analysis (Hayashi, 1980). These analyses are particularly applied to grid-point data on latitude circles. In order to test some physical factors which may affect the generation of tropical transient planetary waves, three different model simulations with the CCM1 (the control, the no-mountain, and the no-cloud experiments) were analyzed.

Cheng, Xinhua↗

NASA NTRS2012

Improvement in Simulation of Eurasian Winter Climate Variability with a Realistic Arctic Sea Ice Condition in an Atmospheric GCM

The present study investigates how much a realistic Arctic sea ice condition can contribute to improve simulation of the winter climate variation over the Eurasia region. Model experiments are set up using different sea ice boundary conditions over the past 24 years (i.e., 1988-2011). One is an atmospheric model inter-comparison (AMIP) type of run forced with observed sea-surface temperature (SST), sea ice, and greenhouse gases (referred to as Exp RSI), and the other is the same as Exp RSI except for the sea ice forcing, which is a repeating climatological annual cycle (referred to as Exp CSI). Results show that Exp RSI produces the observed dominant pattern of Eurasian winter temperatures and their interannual variation better than Exp CSI (correlation difference up to approx. 0.3). Exp RSI captures the observed strong relationship between the sea ice concentration near the Barents and Kara seas and the temperature anomaly across Eurasia, including northeastern Asia, which is not well captured in Exp CSI. Lagged atmospheric responses to sea ice retreat are examined using observations to understand atmospheric processes for the Eurasian cooling response including the Arctic temperature increase, sea-level pressure increase, upper-level jet weakening and cold air outbreak toward the mid-latitude. The reproducibility of these lagged responses by Exp RSI is also evaluated.

sea-ice↗

NASA NTRS2014

Uncertainties in the Modelled CO2 Threshold for Antarctic Glaciation

frequently cited atmospheric CO2 threshold for the onset of Antarctic glaciation of approximately780 parts per million by volume is based on the study of DeConto and Pollard (2003) using an ice sheet model and the GENESIS climate model. Proxy records suggest that atmospheric CO2 concentrations passed through this threshold across the Eocene-Oligocene transition approximately 34 million years. However, atmospheric CO2 concentrations may have been close to this threshold earlier than this transition, which is used by some to suggest the possibility of Antarctic ice sheets during the Eocene. Here we investigate the climate model dependency of the threshold for Antarctic glaciation by performing offline ice sheet model simulations using the climate from 7 different climate models with Eocene boundary conditions (HadCM3L, CCSM3, CESM1.0, GENESIS, FAMOUS, ECHAM5 and GISS_ER). These climate simulations are sourced from a number of independent studies, and as such the boundary conditions, which are poorly constrained during the Eocene, are not identical between simulations. The results of this study suggest that the atmospheric CO2 threshold for Antarctic glaciation is highly dependent on the climate model used and the climate model configuration. A large discrepancy between the climate model and ice sheet model grids for some simulations leads to a strong sensitivity to the lapse rate parameter.

simulation↗

NASA NTRS2013

Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.

Roberts, Yolanda, L.↗

NASA NTRS1999

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Fox-Rabinovitz, Michael S.↗

NASA NTRS2020

The Pliocene Model Intercomparison Project Phase 2: Large-scale Climate Features and Climate Sensitivity

The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ∘C over land and 2.8 ∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60∘ N and 60∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

Pliocene Model Intercomparison Project↗

NASA NTRSDate not supplied

Overview of Large-Scale Transport into the Arctic in the Chemistry Climate Model Initiative (CCMI) Simulations

The transport of trace gases and aerosols is a major uncertainty in the modeling of Arctic tropospheric composition. Here we compare the large-scale midlatitude-to-Arctic transport properties among different models participating in the Chemistry Climate Modeling Initiative (CCMI). Among simulations of the recent past (1980-2010) we show that there are substantial (~30-45%) differences in transport to the Arctic free troposphere, as diagnosed through use of idealized tracers emitted over the Northern Hemisphere (NH) midlatitude surface and subject to prescribed uniform loss. In addition, we show that the spread among tracers with predominantly land-based sources is correlated with the spread in the location of the Hadley Cell edge, while the spread in tracers with zonally uniform sources is also related to differences in (parameterized) convection over oceans. Interestingly, comparisons with simulations constrained with analysis fields reveal similar, if not larger, transport differences, compared to the free-running simulations, indicating that caution should be taken when interpreting simulations constrained with analyzed winds. Finally, among simulations of the 21st century we show that models project a consistent, albeit small (~5-10%), increase in transport from the NH midlatitude surface to the Arctic upper troposphere.

Large-Scale Transpor↗

NASA NTRS2014

Volcanic Contribution to Decadal Changes in Tropospheric Temperature

Despite continued growth in atmospheric levels of greenhouse gases, global mean surface and tropospheric temperatures have shown slower warming since 1998 than previously. Possible explanations for the slow-down include internal climate variability, external cooling influences and observational errors. Several recent modelling studies have examined the contribution of early twenty-first-century volcanic eruptions to the muted surface warming. Here we present a detailed analysis of the impact of recent volcanic forcing on tropospheric temperature, based on observations as well as climate model simulations. We identify statistically significant correlations between observations of stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without the effects of early twenty-first-century volcanic eruptions overestimate the tropospheric warming observed since 1998. In two simulations with more realistic volcanic influences following the 1991 Pinatubo eruption, differences between simulated and observed tropospheric temperature trends over the period 1998 to 2012 are up to 15% smaller, with large uncertainties in the magnitude of the effect. To reduce these uncertainties, better observations of eruption-specific properties of volcanic aerosols are needed, as well as improved representation of these eruption-specific properties in climate model simulations.

Atmospheric temperature↗