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At least 217 records · Page 12

An introduction to three-dimensional climate modeling

The development and use of three-dimensional computer models of the earth's climate are discussed. The processes and interactions of the atmosphere, oceans, and sea ice are examined. The basic theory of climate simulation which includes the fundamental equations, models, and numerical techniques for simulating the atmosphere, oceans, and sea ice is described. Simulated wind, temperature, precipitation, ocean current, and sea ice distribution data are presented and compared to observational data. The responses of the climate to various environmental changes, such as variations in solar output or increases in atmospheric carbon dioxide, are modeled. Future developments in climate modeling are considered. Information is also provided on the derivation of the energy equation, the finite difference barotropic forecast model, the spectral transform technique, and the finite difference shallow water waved equation model.

Washington, W. M.↗

Representations of the Stratospheric Polar Vortices in Versions 1 and 2 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM)

This study will document the behavior of the polar vortices in two versions of the GEOS CCM. Both versions of the model include the same stratospheric chemistry, They differ in the underlying circulation model. Version 1 of the GEOS CCM is based on the Goddard Earth Observing System, Version 4, general circulation model which includes the finite-volume (Lin-Rood) dynamical core and physical parameterizations from Community Climate Model, Version 3. GEOS CCM Version 2 is based on the GEOS-5 GCM that includes a different tropospheric physics package. Baseline simulations of both models, performed at two-degree spatial resolution, show some improvements in Version 2, but also some degradation, In the Antarctic, both models show an over-persistent stratospheric polar vortex with late breakdown, but the year-to-year variations that are overestimated in Version I are more realistic in Version 2. The implications of this for the interactions with tropospheric climate, the Southern Annular Mode, will be discussed. In the Arctic both model versions show a dominant dynamically forced variabi;ity, but Version 2 has a persistent warm bias in the low stratosphere and there are seasonal differences in the simulations. These differences will be quantified in terms of climate change and ozone loss. Impacts of model resolution, using simulations at one-degree and half-degree, and changes in physical parameterizations (especially the gravity wave drag) will be discussed.

Pawson, S.↗

A Saturnian stratospheric seasonal climate model

Motivated by recent observational evidence that seasonal processes occur within Saturn's stratosphere, a seasonal stratospheric climate model has been constructed. This model predicts stratospheric temperatures above the P = 0.1-atm level as a function of time throughout the Saturnian year. Specific results are presented for south-polar and equatorial temperatures. The model predicts that substantial seasonal phase lags exist; maximum stratospheric temperatures at the south pole occur at the southern hemisphere's autumnal equinox. Brightness temperature observations at 17.8 microns, taken during 1977/1978, indicate that stratospheric temperatures are greater at the south pole than at the equator. The model is consistent with these observations, predicting enhanced south polar temperatures, relative to the equator, from 1975 to 1983.

Cess, R. D.↗

An Assessment of the Potential Predictability of Interannual and Decadal Variability Based on Climate Model Simulations with Specified SST

The USCLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. The runs were done with several global atmospheric models including NASA/NSIPP-1, NCEP/GFS, GFDL/AM2, and NCAR CCM3 and CAM3.5. Here we focus on the potential predictability associated with the leading patterns of inter-annual and decadal Pacific SST variability. Specific issues addressed include the nature of the seasonality and regionality of the signal, the noise, and the signal-to-noise ratios, as well as the dependence of the results on the models.

Schubert, Siegfried↗

Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models

Broad-band parameterizations for atmospheric radiative transfer were developed for clear and cloudy skies. These were in the shortwave and longwave regions of the spectrum. These models were compared with other models in an international effort called ICRCCM (Intercomparison of Radiation Codes for Climate Models). The radiation package developed was used for simulations of a General Circulation Model (GCM). A synopsis is provided of the research accomplishments in the two areas separately. Details are available in the published literature.

HARSHVARDHAN↗

How Do Climate Model Resolution and Atmospheric Moisture Affect the Simulation of Unprecedented Extreme Events Like the 2021 Western North American Heat Wave?

Abstract Although the 2021 Western North America (WNA) heat wave was predicted by weather forecast models, questions remain about whether such strong events can be simulated by global climate models (GCMs) at different model resolutions. Here, we analyze sets of GCM simulations including historical and future periods to check for the occurrence of similar events. High‐ and low‐resolution simulations both encounter challenges in reproducing events as extreme as the observed one, particularly under the present climate. Relatively stronger amplitudes are observed during the future periods. Furthermore, high‐ and low‐resolution short initialized GCM simulations are both able to reasonably predict such strong events and their associated high‐pressure ridge over the WNA with a 1 week forecast lead time. Moisture sensitivity experiments further indicate a drier atmospheric moisture condition results in substantially higher near‐surface temperatures in the simulated heat events.

54 ENVIRONMENTAL SCIENCES↗

CERESMIP: A Climate Modeling Protocol to Investigate Recent Trends in the Earth's Energy Imbalance

The Clouds and the Earth's Radiant Energy System (CERES) project has now produced over two decades of observed data on the Earth's Energy Imbalance (EEI) and has revealed substantive trends in both the reflected shortwave and outgoing longwave top-of-atmosphere radiation components. Available climate model simulations suggest that these trends are incompatible with purely internal variability, but that the full magnitude and breakdown of the trends are outside of the model ranges. Unfortunately, the Coupled Model Intercomparison Project (Phase 6) (CMIP6) protocol only uses observed forcings to 2014 (and Shared Socioeconomic Pathways (SSP) projections thereafter), and furthermore, many of the ‘observed' drivers have been updated substantially since the CMIP6 inputs were defined. Most notably, the sea surface temperature (SST) estimates have been revised and now show up to 50% greater trends since 1979, particularly in the southern hemisphere. Additionally, estimates of short-lived aerosol and gas-phase emissions have been substantially updated. These revisions will likely have material impacts on the model-simulated EEI. We therefore propose a new, relatively low-cost, model intercomparison, CERESMIP, that would target the CERES period (2000-present), with updated forcings to at least the end of 2021. The focus will be on atmosphere-only simulations, using updated SST, forcings and emissions from 1990 to 2021. The key metrics of interest will be the EEI and atmospheric feedbacks, and so the analysis will benefit from output from satellite cloud observation simulators. The Tier 1 request would consist only of an ensemble of AMIP-style simulations, while the Tier 2 request would encompass uncertainties in the applied forcing, atmospheric composition, single and all-but-one forcing responses. We present some preliminary results and invite participation from a wide group of models.

CMIP6↗

Projected Impact of Climate Change on the Energy Budget of the Arctic Ocean by a Global Climate Model

The annual energy budget of the Arctic Ocean is characterized by a net heat loss at the air-sea interface that is balanced by oceanic heat transport into the Arctic. The energy loss at the air-sea interface is due to the combined effects of radiative, sensible, and latent heat fluxes. The inflow of heat by the ocean can be divided into two components: the transport of water masses of different temperatures between the Arctic and the Atlantic and Pacific Oceans and the export of sea ice, primarily through Fram Strait. Two 150-year simulations (1950-2099) of a global climate model are used to examine how this balance might change if atmospheric greenhouse gases (GHGs) increase. One is a control simulation for the present climate with constant 1950 atmospheric composition, and the other is a transient experiment with observed GHGs from 1950 to 1990 and 0.5% annual compounded increases of CO2 after 1990. For the present climate the model agrees well with observations of radiative fluxes at the top of the atmosphere, atmospheric advective energy transport into the Arctic, and surface air temperature. It also simulates the seasonal cycle and summer increase of cloud cover and the seasonal cycle of sea-ice cover. In addition, the changes in high-latitude surface air temperature and sea-ice cover in the GHG experiment are consistent with observed changes during the last 40 and 20 years, respectively. Relative to the control, the last 50-year period of the GHG experiment indicates that even though the net annual incident solar radiation at the surface decreases by 4.6 W(per square meters) (because of greater cloud cover and increased cloud optical depth), the absorbed solar radiation increases by 2.8 W(per square meters) (because of less sea ice). Increased cloud cover and warmer air also cause increased downward thermal radiation at the surface so that the net radiation into the ocean increases by 5.0 Wm-2. The annual increase in radiation into the ocean, however, is compensated by larger increases in sensible and latent heat fluxes out of the ocean. Although the net energy loss from the ocean surface increases by 0.8 W (per square meters), this is less than the interannual variability, and the increase may not indicate a long-term trend. The seasonal cycle of heat fluxes is significantly enhanced. The downward surface heat flux increases in summer (maximum 2 of 19 W per square meters or 23% in June) while the upward heat flux increases in winter (maximum of 16 W per square meters or 28% in November). The increased downward flux in summer is due to a combination of increases in absorbed solar and thermal radiation and smaller losses of sensible and latent heat. The increased heat loss in winter is due to increased sensible and latent heat fluxes, which in turn are due to reduced sea-ice cover. On the other hand, the seasonal cycle of surface air temperature is damped, as there is a large increase in winter temperature but little change in summer.

Miller, James R.↗

Cloud-radiation interactions and their parameterization in climate models

This report contains papers from the International Workshop on Cloud-Radiation Interactions and Their Parameterization in Climate Models met on 18-20 October 1993 in Camp Springs, Maryland, USA. It was organized by the Joint Working Group on Clouds and Radiation of the International Association of Meteorology and Atmospheric Sciences. Recommendations were grouped into three broad areas: (1) general circulation models (GCMs), (2) satellite studies, and (3) process studies. Each of the panels developed recommendations on the themes of the workshop. Explicitly or implicitly, each panel independently recommended observations of basic cloud microphysical properties (water content, phase, size) on the scales resolved by GCMs. Such observations are necessary to validate cloud parameterizations in GCMs, to use satellite data to infer radiative forcing in the atmosphere and at the earth's surface, and to refine the process models which are used to develop advanced cloud parameterizations.

Source record↗

An Assessment of the Potential Predictability of Drought Over the United States Based on Climate Model Simulations with Specified SST

The USCLIV AR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. The runs were done with several global atmospheric models including NASA/NSIPP-l, NCEP/GFS, GFDLlAM2, and NCAR CCM3 and CAM3.5. Specific questions that the runs are designed to address include: What are mechanisms that maintain drought across the seasonal cycle and from one year to the next. To what extent can droughts develop independently of ocean variability due to year-to-year memory that may be inherent to the land. What is the role of the different ocean basins? Here we focus on the potential predictability of drought conditions over the United States. Specific issues addressed include the seasonality and regionality of the signal-to-noise ratios associated with Pacific and Atlantic SST forcing, and the sensitivity of the results to the climatological stationary waves simulated by the different AGCMs.

Schubert, Siegfried↗

Middle Atmosphere Response to Different Descriptions of the 11-Year Solar Cycle in Spectral Irradiance in a Chemistry-Climate Model

The 11-year solar cycle in solar spectral irradiance (SSI) inferred from measurements by the SOlar Radiation & Climate Experiment (SORCE) suggests a much larger variation in the ultraviolet than previously accepted. We present middle atmosphere ozone and temperature responses to the solar cycles in SORCE SSI and the ubiquitous Naval Research Laboratory (NRL) SSI reconstruction using the Goddard Earth Observing System chemistry-climate model (GEOS CCM). The results are largely consistent with other recent modeling studies. The modeled ozone response is positive throughout the stratosphere and lower mesosphere using the NRL SSI, while the SORCE SSI produces a response that is larger in the lower stratosphere but out of phase with respect to total solar irradiance above 45 km. The modeled responses in total ozone are similar to those derived from satellite and ground-based measurements, 3-6 Dobson Units per 100 units of 10.7-cm radio flux (F10.7) in the tropics. The peak zonal mean tropical temperature response 50 using the SORCE SSI is nearly 2 K per 100 units 3 times larger than the simulation using the NRL SSI. The GEOS CCM and the Goddard Space Flight Center (GSFC) 2-D coupled model are used to examine how the SSI solar cycle affects the atmosphere through direct solar heating and photolysis processes individually. Middle atmosphere ozone is affected almost entirely through photolysis, whereas the solar cycle in temperature is caused both through direct heating and photolysis feedbacks, processes that are mostly linearly separable. Further, the net ozone response results from the balance of ozone production at wavelengths less than 242 nm and destruction at longer wavelengths, coincidentally corresponding to the wavelength regimes of the SOLar STellar Irradiance Comparison Experiment (SOLSTICE) and Spectral Irradiance Monitor (SIM) on SORCE, respectively. A higher wavelength-resolution analysis of the spectral response could allow for a better prediction of the atmospheric response to arbitrary SSI variations.

Swartz, W. H.↗

Extratropical Cyclone Clouds in the GFDL Climate Model: Diagnosing Biases and the Associated Causes

The clouds in southern hemisphere extratropical cyclones generated by the GFDL climate model are analyzed against MODIS, CloudSat and CALIPSO cloud and precipitation observations. Two model versions are used: one is a developmental version of AM4, a model GFDL will utilize for CMIP6, the other is the same model with a different parameterization of moist convection. Both model versions predict a realistic top-of-atmosphere cloud cover in the southern oceans, within 5% of the observations. However, an examination of cloud cover transects in extratropical cyclones reveals a tendency in the models to overestimate high-level clouds (by differing amounts) and underestimate cloud cover at low-levels (again by differing amounts), especially in the post-cold frontal (PCF) region, when compared to observations. Focusing on only the models, their differences in high and mid-level clouds are consistent with their differences in convective activity and relative humidity (RH), but the same is not true for the PCF region. In this region, RH is higher in the model with less cloud fraction. These seemingly contradictory cloud and RH differences can be explained by differences in the cloud parameterization tuning parameters that ensure radiative balance. In the PCF region, the model cloud differences are smaller than either of the model biases with respect to observations, suggesting other physics changes are needed to address the bias. The process-oriented analysis used to assess these model differences will soon be automated and shared.

Catherine M Naud↗

Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment

Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation.

Skiles, J. W.↗

Photon Harvesting and Rocky Planet Biosignatures with 3D Climate Models

On the Earth solar photons are collected, sifted, and harvested by life at a scale that has transformed and defined the planet and continues to do so. That transformation is considered to be a key biosignature to look for in the rocky exoplanet population of our galaxy. However, the availability of photons on planetary surfaces depends on orbital and spin configuration as well as shadowing and scattering by clouds and other atmospheric phenomena. We are using a state-of-the-art 3D climate model (ROCKE-3D, Way et al. 2017) to study rocky planet surface irradiances and the implications for biosignatures and future missions such as the Habitable Worlds Observatory.

exoplanets↗

The Impact of Different Absolute Solar Irradiance Values on Current Climate Model Simulations

Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.

climate change↗

A Systematic Approach to Isolating the Causes and Impacts of Climate Model Bias Employing Analysis Increments

One of the most promising approaches to isolating the causes and understanding the impacts of climate model formulation errors is through the utilization of information contained in short-term forecast errors. The underlying assumption being that by capturing the errors at the very early stages of growth (before nonlinearities develop), we should be able to associate those errors with specific deficiencies in the model's formulation of the relevant physical processes. Here, we provide an example of utilizing the long-term mean of the 6-hourly analysis increments (first guess forecast minus analysis) produced by MERRA-2 to correct the NASA/GEOS AGCM over well-defined regions, thereby allowing us to quantify how the reduced tendency errors in these regions manifest themselves both locally and remotely through large-scale teleconnections to reduce the model's climatological biases. We extend previous work (focused on boreal summer) to address the full annual cycle of model bias. A key result is the large seasonality of the errors over the Tibet region and their impacts on the Northern Hemisphere jet biases, and related precipitation and temperature biases over North American. Attempts to correct the phase and amplitude errors of the climatological boreal winter ridge over western North America (a likely key requirement for improving winter climate forecasts over North America) reveal a surprising complexity in the sources of the errors in what is otherwise manifest as a rather simple PNA-like bias structure.

Schubert, S.↗

Bering Strait Ocean Heat Transport Drives Decadal Arctic Variability in a High‐Resolution Climate Model

Abstract We investigate the role of ocean heat transport (OHT) in driving the decadal variability of the Arctic climate by analyzing the pre‐industrial control simulation of a high‐resolution climate model. While the OHT variability at 65°N is greater in the Atlantic, we find that the decadal variability of Arctic‐wide surface temperature and sea ice area is much better correlated with Bering Strait OHT than Atlantic OHT. In particular, decadal Bering Strait OHT variability causes significant changes in local sea ice cover and air‐sea heat fluxes, which are amplified by shortwave feedbacks. These heat flux anomalies are regionally balanced by longwave radiation at the top of the atmosphere, without compensation by atmospheric heat transport (Bjerknes compensation). The sensitivity of the Arctic to changes in OHT may thus rely on an accurate representation of the heat transport through the Bering Strait, which is difficult to resolve in coarse‐resolution ocean models.

54 ENVIRONMENTAL SCIENCES↗

A Tropospheric Emission Spectrometer HDO/H2O Retrieval Simulator for Climate Models

Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the model meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, categorical approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and model meteorology at short time scales. To test this approach, nudged simUlations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the D fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30 over the ocean and decreases of up to 40 over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had D biases of 8 over ocean and 34 over land compared to TES D, which were less than the biases using raw model D fields.

Field, R. D.↗