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To test the influence of the ground moisture on the summertime climate the GISS general circulation model is used. The version used had 8 x 10 deg horizontal resolution and 9 layers in the vertical. This version produces a good simulation of the current climate.
The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables?e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.
Several global climate simulations by the 7-layer, 8 x 10 GISS climate model were designed to test the contributions of various surface boundary conditions to the global climate. The model was run with the sun fixed at a perpetual January. In a comparison of run #5, in which realistic January surface boundary conditions were used, with run #4, which was the same except that a zonally symmetric climatological January sea surface temperature (SST) field was used, one of the results was that run #5 provided a better simulation of the Indian Ocean monsoon. A further comparison of the wind fields over the Indian Ocean that were generated by these two model runs is presented.
A numerical scheme is specifically designed to develop a time-dependent climate model to ensure the conservation of mass, momentum, energy, and water vapor, in order to study the biogeophysical feedback for the climate of Africa. A vegetation layer is incorporated in the present two-dimensional climate model. Using the coupled climate-vegetation model, two tests were performed involving the removal and expansion of the Sahara Desert. Results show that variations in the surface conditions produce a significant feedback to the climate system. It is noted that the simulation responses to the temperature and zonal wind in the case of an expanded desert agree with the climatological data for African dry years. Perturbed simulations have also been performed by changing the albedo only, without allowing the variation in the vegetation layer. It is shown that the variation in latent heat release is significant and is related to changes in the vegetation cover. As a result, precipitation and cloud cover are reduced.
On 15th Jan. 2022 the submarine Hunga volcano erupted injecting approximately 0.5 Tg of sulfur dioxide into the stratosphere, but more significantly added 150-170 Tg of water vapor to the stratospheric background (over a 10% perturbation) in a matter of several hours. The sulfur dioxide rapidly converted to sulfate aerosol and along with water vapor, was transported around the Southern Hemisphere sub-tropics into midlatitudes and beyond with some transport into the Northern Hemisphere. With a much longer lifetime than sulfate aerosol, measurable water vapor mass anomalies have persisted with only small losses over more than 2 years since the eruption and are likely to continue above background for the remainder of the decade. Satellite measurements from limb and nadir viewing observing instruments provide the information needed to reasonably initialize the Hunga eruption in the Goddard Earth Observing System (GEOS) model using the “replay” framework coupled to the Global Modeling Initiative (GMI) stratosphere-troposphere chemical mechanism for the recent past and have continued the simulations into the future with the free running chemistry climate model (CCM). Using a number of model ensemble members together with the satellite observations, we quantify how the Hunga eruption is perturbing atmospheric composition and climate and projecting the influences to come as the enhanced water vapor continues in the stratosphere with only very slow removal mechanisms. Modeling suggests that the water rich eruption enhanced stratospheric hydroxyl radiacal (OH) and is supported by the speed of the observed conversion of SO2 into sulfate aerosol. These simulations also suggest a significant reduction in tropospheric OH over the mid-high latitude Southern Hemisphere, which has implications for numerous species that are impacted by this radical. The Hunga eruption provides a useful test of chemistry climate models and an opportunity for observation-based process understanding and in making new connections.
On 15th Jan. 2022 the submarine volcano Hunga Tonga-Hunga Ha’apai (HTHH) injected approximately 0.5 Tg of sulfur dioxide into the stratosphere, but more significantly added 150-170 Tg of water vapor to the stratospheric background (over a 10% perturbation) in a matter of several hours. The sulfur dioxide rapidly converted to sulfate aerosol and along with water vapor, was transported around the Southern Hemisphere sub-tropics into midlatitudes with some transport into the Northern Hemisphere. With a much longer lifetime than sulfate aerosol, measurable water vapor mass anomalies have persisted with only small losses over the past almost 2 years and are likely to continue above background for the remainder of the decade. Satellite measurements from limb and nadir viewing observing instruments provide the information needed to reasonably initialize the HTHH eruption in the Goddard Earth Observing System (GEOS) model using the “replay” framework coupled to the Global Modeling Initiative (GMI) stratosphere-troposphere chemical mechanism for the recent past and continue the simulations into the future with the free running chemistry climate model (CCM). Using a number of model ensemble members together with the satellite observations, we quantify how the HTHH eruption is perturbing stratospheric composition and climate and projecting the influences to come as the enhanced water vapor continues in the stratosphere with only very slow removal mechanisms. HTHH eruption provides a useful test of chemistry climate models and an opportunity for observation-based process understanding, which we will highlight.
Preliminary steps were taken to develop a climate model adequate for seasonal and interannual simulations. Tests of the model against the observed seasonal cycle of key climate properties indicate an encouraging capability for climate applications.
A three-part microwave T(B) brightness temperature model was tested for applicability in regions of differing climatic and vegetation regime. Model parameters were limited to vegetation in the form of the normalized vegetation index (NDVI) and climatically modeled soil moisture. The T(B) model was calibrated for two climatically contrasting areas and subsequently validated on different test sites of similar climatic character. Vegetative characteristics in the form of the mean NDVI was used to partition and lump data from different test sites. Good agreement was realized between estimated T(B) and Nimbus-7 SMMR T(B) at the 6.6 GHz horizontal channel.
The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.
We describe and review recent upgrades to the ARC Mars climate modeling framework, in particular, with regards to physical parameterizations (i.e., testing, implementation, modularization and documentation); the current climate modeling capabilities; selected research topics regarding current/past climates; and then, our near-term plans related to the NASA ARC Mars general circulation modeling (GCM) project.
The Green Sahara Period, spanning about 11,500 to 5,000 years ago, offers an opportunity to test the ability of climate models to simulate large-scale changes in northern African climate through the strengthening of the West African Monsoon. In this study, we evaluate the performance of four models in simulating the mid-Holocene (6,000 BP), namely – EC-Earth, iCESM, CCSM4-Toronto, and the GISS ModelE2.1-G. Two scenarios are considered for each model – a standard PMIP scenario simulated with the mid-Holocene orbital parameters and greenhouse gas concentrations with vegetation prescribed to pre-industrial conditions, as well as a Green-Sahara scenario which additionally considers factors such as enhanced vegetation, reduced dust, presence of lakes, and land and soil feedbacks. All mid-Holocene scenarios capture an increase in monsoonal precipitation in northern Africa. However, a comparison of the two mid-Holocene scenarios reveals significantly higher precipitation in northern Africa for all the Green-Sahara scenarios relative to the PMIP scenarios – an observation consistent across all models. Accompanied by a strengthened Saharan Heat Low, these changes in the West African Monsoon are also linked to polar amplification, a stronger Indian Summer Monsoon and alterations to the Walker circulation. Model results are in agreement with pollen-based SAT records, multi-proxy SST records and African lake level records. This comparison indicates that a realistic simulation of the mid-Holocene Green Sahara requires consideration of multiple factors in addition to orbital and greenhouse gas forcings.
A major motivation for the study of the coupled land-atmosphere system is the idea that soil moisture anomalies may affect future meteorological variables through their effects on future surface energy and water budgets. If true, the accurate initialization of soil moisture in a subseasonal or seasonal forecast system may improve forecast skill, making the forecast products more valuable to society. The Global Land-Atmosphere Coupling Experiment (GLACE-2) project is examining, with a wide variety of models, the degree to which subseasonal (out to two months) precipitation and air temperature forecasts improve through the realistic initialization of soil moisture. For the first time ever, a global consensus should emerge regarding the value of land initialization for forecasts, perhaps motivating national forecast centers to make full use of land moisture initialization in their operations. Participants in GLACE-2 perform two series of forecasts, each consisting of 100 2-month forecast ensembles (10 members per ensemble) covering ten boreal spring and summer start-dates in each of the years 1986-1995. Series 1 utilizes realistic land surface state initialization, provided through a decadal offline simulation using realistic meteorological forcing, as provided by the Global Soil Wetness Project - Phase 2 (GSWP-2), a research activity of the Global Land-Atmosphere System Study (GLASS) of GEWEX. Series 2 is identical to Series 1 in every way except for the fact that it does not benefit from realistic land state initialization. Through the comparison of Series 1 and 2, we isolate the impact of land initialization on the forecasts. Optional extensions to these base runs include forecasts covering additional years, using alternative meteorological forcing for the land initialization. To date, GLACE-2 has garnered participation from eleven modeling groups, covering 13 atmospheric models. Analysis of available results is already well underway, both at the individual modeling institutions and at the NASA Goddard Space Flight Center, which is coordinating the project. Analysis focuses on two elements of the forecast problem: (i) the quantification of model-specific "predictability" (i.e., the degree to which simulated atmospheric chaos will foil a forecast, even under the assumption of"perfect" model physics, initialization data, and validation data) and its decay with time; and (ii) the quantification of forecast skill, determined through a comparison of predicted precipitation and air temperature against observations. Indeed, the specific contribution of land initialization to both these elements is isolated through a comparison of the Series 1 and 2 forecasts. We examine the two elements at four different forecast leads: 1-15, 16-30, 31-45, and 46-60 days. Statistics-based approaches for enhancing skill (essentially using observational statistics to reduce the impact of the models' climatic biases) are also tested. In the present talk, we provide an update of progress in GLACE-2, featuring quantifications of predictability and forecast skill for a number of the participating models and providing a "first look" at the desired consensus view of land impacts on subseasonal forecasts.
Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.
• The challenge for us at COSPAR in putting this program together was that we are primarily a scientifically oriented organization. “Climate Action,” as it is often expressed publicly, tends to be the domain of “activists.” As scientists, on the other hand, to retain our credibility – and for the contributions we make to continue carrying the weight of scientific truth – it is critical that we remain even-handed in our analysis and our reporting of results. • COSPAR is the Committee on Space Research, and fortunately, much of what we observe from space bears objectively on the attributes of the Earth System and how it is evolving. We can measure from space changes in the cryosphere, in the oceans, the land surface and the atmosphere, frequently, on a global scale, to a degree that is generally not possible any other way. And we have been making such observations, in increasing detail, scope, and precision, for about 60 years. • These data help us characterize the current state and identify patterns of change in the Earth System that allow us to infer processes and to improve climate models. With modeling we can test and refine our inferences, and make some predictions. The results can then inform policy and decision-makers, the public in general, as well as those taking direct action. • So, for today’s session we have invited 7 15-minute presentations spanning a broad range of climate-related topics, covering observations from space that can inform climate-related decision-making – from sea-ice extent and sea-level rise, to land surface properties and land-based water resources, to interactions between land or water surfaces and the atmosphere, to severe events in the atmosphere itself. • We begin with an overview of the observations contributed by one of the premier space agencies, given by NASA Chief Scientist and Senior Climate Advisor Dr. Kate Calvin, which will be followed by talks on what we are learning about specific attributes of the Earth System from space-based measurements that can inform climate-related policy and action.
Radiative forcing is defined as the change in the net (downwelling minus upwelling) radiative flux at a given level in the atmosphere. This net flux is the radiative power density available to drive climatic processes in the earth-atmosphere system below that level. Recent research shows that radiative forcing by aerosol particles is a major source of uncertainty in climate predictions. To reduce those uncertainties, TARFOX was designed to determine direct (cloud-free) radiative forcing by the aerosols in one of the world's major industrial pollution plumes--that flowing from the east coast of the US over the Atlantic Ocean. TARFOX measured a variety of aerosol radiative effects (including direct forcing) while simultaneously measuring the chemical, physical, and optical properties of the aerosol particles causing those effects. The resulting data sets permit a wide variety of tests of the consistency, or closure, among the measurements and the models that link them. Because climate predictions use the same or similar model components, closure tests help to assess and reduce prediction uncertainties. In this work we use the TARFOX-determined aerosol, gas, and surface properties to compute radiative forcing for a variety of aerosol episodes, with inadvisable optical depths ranging from 0.07 to 0.6. We calculate forcing by several techniques with varying degrees of sophistication, in part to test the range of applicability of simplified techniques--which are often the only ones feasible in climate predictions by general circulation models (GCMs). We then compare computed forcing to that determined from: (1) Upwelling and downwelling fluxes (0.3-0.7 mm and 0.7-3.0 mm) measured by radiometers on the UK MRF C-130. and (2) Daily average cloud-free absorbed solar and emitted thermal radiative flux at the top of the atmosphere derived from the AVHRR radiometer on the NOAA- 14 satellite. The calculations and measurements all yield aerosol direct radiative forcing in the range -50 to -190 W sq m per unit inadvisable optical depth. The magnitudes are about 15 to 100 times larger than the global-average direct forcing expected for the global-average sulfate aerosol optical depth of 0.04. The reasons for the larger forcing in TARFOX include the relatively large optical depths and the focus on cloud-free, daytime conditions over the dark ocean surface. These are the conditions that produce the actual major radiative forcing events that contribute to any global-average climate effect. Detailed comparisons of calculated and measured forcings for specific events are used for more refined tests of closure.
The effects of the 1963 Mt. Agung (Bali) volcanic eruption are studied with respect to the response of the climate system to global radiative perturbations. Volcanic aerosols, spread globally by stratospheric winds, cause a perturbation characterized by a reasonably well known forcing function. Since the climatic response to a large eruption should be pronounced, these phenomena might provide a means to test the validity of climate models. The Mt. Agung eruption is described, and the atmospheric thermal response is calculated. The magnitude, sign, and time delay of temperature changes computed with a simple one-dimensional climate model for both the stratosphere and troposphere are in agreement with the observed temperature changes.
Tropical rainfall data are crucial in determining the role of tropical latent heating in driving the circulation of the global atmosphere. Also, the data are particularly important for testing the realism of climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the effects of El Nino on climate could be addressed with a reliable, extended time series of tropical rainfall observations. A passive microwave sensor is planned to provide information on the integrated column precipitation content, its areal distribution, and its intensity. An active microwave sensor (radar) will define the layer depth of the precipitation and provide information about the intensity of rain reaching the surface, the key to determining the latent heat input to the atmosphere. A visible/infrared sensor will provide very high resolution information on cloud coverage, type, and top temperatures and also serve as the link between these data and the long and virtually continuous coverage by the geosynchronous meteorological satellites. The unique combination of sensor wavelengths, coverages, and resolving capabilities together with the low-altitude, non-Sun synchronous orbit provide a sampling capability that should yield monthly precipitation amounts to a reasonable accuracy over a 500- by 500-km grid.
The objective of this investigation has been to examine the mass and momentum exchange between the atmosphere, oceans, solid Earth, hydrosphere, and cryosphere. The investigation has focused on changes in the Earth's gravity field, its rotation rate, atmospheric and oceanic circulation, global sea level change, ice sheet change, and global ground water circulation observed by contemporary sensors and models. The primary component of the mass exchange is water. The geodetic observables provided by these satellite sensors are used to study the transport of water mass in the hydrological cycle from one component of the Earth to another, and they are also used to evaluate the accuracy of models. As such, the investigation is concerned with the overall global water cycle. This report provides a description of scientific, educational and programmatic activities conducted during the period July 1, 1999 through June 30,2000. Research has continued into measurements of time-varying gravity and its relationship to Earth rotation. Variability of angular momentum and the related excitation of polar motion and Earth rotation have been examined for the atmosphere and oceans at time-scales of weeks to several years. To assess the performance of hydrologic models, we have compared geodetic signals derived from them with those observed by satellites. One key component is the interannual mass variability of the oceans obtained by direct observations from altimetry after removing steric signals. Further studies have been conducted on the steric model to quantify its accuracy at global and basin-scales. The results suggest a significant loss of water mass from the Oceans to the land on time-scales longer than 1-year. These signals are not reproduced in any of the models, which have poorly determined interannual fresh water fluxes. Output from a coupled atmosphere-ocean model testing long-term climate change hypotheses has been compared to simulated errors from the Gravity Recovery and Climate Experiment (GRACE) mission. Results indicate that GRACE will be able to observe seasonal signals at half-wavelengths ranging from 1000 to 10000 km, and may be able to observe secular trends at half- wavelengths of greater than 2000-3000 km for soil moisture and snow depth if they are as large as some of the climate experiments predict.