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At least 325 records · Page 18

Additional Contributions to the Development of the New Snow-Physics Scheme for SSiB

The Simplified Simple Biosphere Model (SSiB) had a well-documented problem with snowmelt timing and infiltration. A new snow-physics scheme was developed for use in SSIB. In this, the snow layer is separated from the soil, with its own energy budget and temperature. Solar energy reaching the top of the snowpack is divided into three parts: one, reflected by the snow; two, absorbed by the snow; and three, transmitted to the ground following a simple extinction relation. Heat is exchanged between the ground and snow by conduction and by radiation through an arbitrary air-gap between them. In the GSWP exercise using the GEWEX ISLSCP Initiative I forcing data (hereafter "offline"), it was found that the new snow scheme ameliorated a significant fraction of snowmelt time-delay as compared to observations from satellite. It also produced warmer ground temperatures under the snowpack, which allowed realistic meltwater infiltration, resulting in better simulated spring soil moisture recharge and peak runoff amount as compared to observations. An ensemble of six June-July-August (JJA) simulations for 1987 and 1988 were performed with the NASA Goddard GEOS II GCM coupled with the new snow-physics SSIB using new initial soil moisture (ISM) from the offline simulations. The GCM produced more realistic precipitation in northern regions that had large snowmelt and wetter ISM in response to better snow-physics, as compared to simulations with ISM without the new snow scheme. The new SSiB-GCM also increased the interannual precipitation signal in the Indian monsoon region, resulting from changes in ISM in the Himalayas and central Asia.

Mocko, David M.↗

Seasonal-to-Interannual Precipitation Variability and Predictability in a Coupled Land-Atmosphere System

In an earlier GCM study, we showed that interactive land surface processes generally contribute more to continental precipitation variance than do variable sea surface temperatures (SSTs). A new study extends this result through an analysis of 16-member ensembles of multi-decade GCM simulations. We can now show that in many regions, although land processes determine the amplitude of the interannual precipitation anomalies, variable SSTs nevertheless control their timing. The GCM data can be processed into indices that describe geographical variations in (1) the potential for seasonal-to-interannual prediction, and (2) the extent to which the predictability relies on the proper representation of land-atmosphere feedback.

Koster, Randal D.↗

DAO's Next Generation Physical-Space/Finite-Volume Data Assimilation System: Formulation and Initial Evaluation

The Physical-space/Finite-volume Data Assimilation System (fvDAS) is the next generation global atmospheric data assimilation system in development at the Data Assimilation Office at NASA's Goddard Space Flight Center. It is based on a new finite-volume general circulation model jointly developed by NASA and NCAR, and on the Physical-Space Statistical Analysis System (PSAS) developed at the DAO. In this talk we will describe the general system formulation, the adaptive quality control and general aspects of the error covariance modeling. The NASA-NCAR GCM is a completely new model which replaces the CEOs GCM used in the previous GEOS-1/2/3 Data Assimilation systems. A particular configuration of adaptive Statistical Quality Control and the Physical-space Statistical Analysis System (PSAS) are currently implemented in DAO's operational Data Assimilation System. However, the unique finite-volume formulation of the NASA-NCAR GCM, combined with the generality of the observation-space formulation of PSAS, provides for a very simple and accurate model-analysis interface. The system assimilates a variety of conventional and satellite observations. In particular, TOVS Level 1B radiances are assimilated using a 1-D variational scheme, both in clear sky and cloudy conditions. Computationally, the fvDAS runs approximately 10 times faster than the operational GEOS-Terra system. We will show that the next-generation fvDAS has much improved observation-minus-6hr forecast (O-F) statistics, as well as 5-day forecast skills. Top of the atmosphere radiation fields are in closer agreement with CERES measurements, with realistic precipitation and moisture fields. We will also show that the finite-volume formulation of the fvDAS produce assimilated fields which are more suitable for driving constituent transport models.

daSilva, A.↗

A Comparison of the Age-Spectra from Data Assimilation Models

We use kinematic and diabatic back trajectory calculations, driven by winds from a general circulation model (GCM) and two different data assimilation systems (DAS), to compute the age spectrum at three latitudes in the lower stratosphere. The age-spectra are compared to chemical transport model (CTM) calculations, and the mean ages from all of these studies are compared to observations. The age spectra computed using the GCM winds show a reasonably well-isolated tropics in good agreement with observations; however, the age spectra determined from the DAS differ from the GCM spectra. For the diabatic trajectory calculations, the age spectrum is too broad as a result of too much exchange between the tropics and mid-latitudes. The age spectrum determined using the kinematic trajectory calculation is less broad and lacks an age offset; both of these features are due to excessive vertical dispersion of parcels. The tropical and mid-latitude mean age difference between the diabatically and kinematically determined age-spectra is about one year, the former being older. The CTM calculation of the age spectrum using the DAS winds shows the same dispersive characteristics of the kinematic trajectory calculation. These results suggest that the current DAS products will not give realistic trace gas distributions for long integrations; they also help explain why the mean ages determined in a number of previous DAS driven CTM's are too young compared with observations. Finally, we note trajectory-generated age spectra show significant age anomalies correlated with the seasonal cycles, and these anomalies can be linked to year-to-year variations in the tropical heating rate. These anomalies are suppressed in the CTM spectra suggesting that the CTM transport is too diffusive.

Schoeberl, Mark R.↗

A Comparison of the Lower Stratospheric Age-Spectra Derived from a General Circulation Model and Two Data Assimilation Systems

We use kinematic and diabatic back trajectory calculations, driven by winds from a general circulation model (GCM) and two different data assimilation systems (DAS), to compute the age spectrum at three latitudes in the lower stratosphere. The age-spectra are compared to chemical transport model (CTM) calculations, and the mean ages from all of these studies are compared to observations. The age spectra computed using the GCM winds show a reasonably isolated tropics in good agreement with observations; however, the age spectra determined from the DAS differ from the GCM spectra. For the DAS diabatic trajectory calculations there is too much exchange between the tropics and mid-latitudes. The age spectrum is thus too broad and the tropical mean age is too old as a result of mixing older mid latitude air with tropical air. Likewise the mid latitude mean age is too young due to the in mixing of tropical air. The DAS kinematic trajectory calculations show excessive vertical dispersion of parcels in addition to excessive exchange between the tropics and mid latitudes. Because air is moved rapidly to the troposphere from the vertical dispersion, the age spectrum is shifted toward the young side. The excessive vertical and meridional dispersion compensate in the kinematic case giving a reasonable tropical mean age. The CTM calculation of the age spectrum using the DAS winds shows the same vertical and meridional dispersive characteristics of the kinematic trajectory calculation. These results suggest that the current DAS products will not give realistic trace gas distributions for long integrations; they also help explain why the extra tropical mean ages determined in a number of previous DAS driven CTM s are too young compared with observations. Finally, we note trajectory-generated age spectra . show significant age anomalies correlated with the seasonal cycles. These anomalies can be linked to year-to-year variations in the tropical heating rate. The anomalies are suppressed in the CTM spectra suggesting that the CTM transport scheme is too diffusive.

Schoeberl, Mark R.↗

Retrospective Data Assimilation for GEOS-4

The NASA/Goddard Earth Observing System 3 (GEOS-3) has recently been replaced operationally by GEOS-4. One of the major components of the new system is the finite-volume general circulation model (GCM) of Lin and Rood. Updating the GEOS-3 retrospective data assimilation system of Zhu et al. to GEOS-4 requires two main steps: (i) developing the adjoint of the finite-volume GCM; and (ii) developing the adjoint of the procedures interfacing the GCM with the Physical-space Statistical Analysis System. These required adjoints are being developed automatically through the use of the Transformation of Algorithms in Fortran compiler of Giering and Kaminski. In this presentation we discuss the current status of development and plans for the near future as well as show preliminary results.

Todling, Ricardo↗

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

Fox-Rabinovitz, Michael S.↗

Sensitivity of Middle Atmospheric Analysis to the Representation of Gravity Wave Drag

This study examines the sensitivity of middle atmospheric analyses to the representation of gravity wave drag (GWD) in the general circulation model (GCM). A strong sensitivity of temperatures near the stratopause to the inclusion and representation of waves with non-zero phase speeds is isolated; this is consistent with the induced mean meridional circulation. The change (between a control analysis and one with no GWD) decreases with decreasing altitude and has a vertical structure with alternating positive and negative differences that are caused by the constraint on thick-layer radiances offered by near-nadir sounding radiometers. Without the non-zero phase-speed GWI), there is a large observation minus forecast residual that is substantially smaller when these waves are included, indicating the need for these waves in the GCM. Moreover, the sensitivity of analyzed temperatures to the inclusion of these waves reveals the importance of using a non-biased GCM in regions where the observational constraint (thick-layer radiances) is indirect.

Li, Shu-Hua↗

Scanning Backscatter Lidar Observations for Characterizing 4-D Cloud and Aerosol Fields to Improve Radiative Transfer Parameterizations

Clouds have a powerful influence on atmospheric radiative transfer and hence are crucial to understanding and interpreting the exchange of radiation between the Earth's surface, the atmosphere, and space. Because clouds are highly variable in space, time and physical makeup, it is important to be able to observe them in three dimensions (3-D) with sufficient resolution that the data can be used to generate and validate parameterizations of cloud fields at the resolution scale of global climate models (GCMs). Simulation of photon transport in three dimensionally inhomogeneous cloud fields show that spatial inhomogeneities tend to decrease cloud reflection and absorption and increase direct and diffuse transmission, Therefore it is an important task to characterize cloud spatial structures in three dimensions on the scale of GCM grid elements. In order to validate cloud parameterizations that represent the ensemble, or mean and variance of cloud properties within a GCM grid element, measurements of the parameters must be obtained on a much finer scale so that the statistics on those measurements are truly representative. High spatial sampling resolution is required, on the order of 1 km or less. Since the radiation fields respond almost instantaneously to changes in the cloud field, and clouds changes occur on scales of seconds and less when viewed on scales of approximately 100m, the temporal resolution of cloud properties should be measured and characterized on second time scales. GCM time steps are typically on the order of an hour, but in order to obtain sufficient statistical representations of cloud properties in the parameterizations that are used as model inputs, averaged values of cloud properties should be calculated on time scales on the order of 10-100 s. The Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE) provides exceptional temporal (100 ms) and spatial (30 m) resolution measurements of aerosol and cloud backscatter in three dimensions. HARLIE was used in a ground-based configuration in several recent field campaigns. Principal data products include aerosol backscatter profiles, boundary layer heights, entrainment zone thickness, cloud fraction as a function of altitude and horizontal wind vector profiles based on correlating the motions of clouds and aerosol structures across portions of the scan. Comparisons will be made between various cloud detecting instruments to develop a baseline performance metric.

Schwemmer, Geary K.↗

Trace Gas/Aerosol Interactions and GMI Modeling Support

Current global aerosol models use different physical and chemical schemes and parameters, different meteorological fields, and often different emission sources. Since the physical and chemical parameterization schemes are often tuned to obtain results that are consistent with observations, it is difficult to assess the true uncertainty due to meteorology alone. Under the framework of the NASA global modeling initiative (GMI), the differences and uncertainties in aerosol simulations (for sulfate, organic carbon, black carbon, dust and sea salt) solely due to different meteorological fields are analyzed and quantified. Three meteorological datasets available from the NASA DAO GCM, the GISS-II' GCM, and the NASA finite volume GCM (FVGCM) are used to drive the same aerosol model. The global sulfate and mineral dust burdens with FVGCM fields are 40% and 20% less than those with DAO and GISS fields, respectively due to its heavier rainfall. Meanwhile, the sea salt burden predicted with FVGCM fields is 56% and 43% higher than those with DAO and GISS, respectively, due to its stronger convection especially over the Southern Hemispheric Ocean. Sulfate concentrations at the surface in the Northern Hemisphere extratropics and in the middle to upper troposphere differ by more than a factor of 3 between the three meteorological datasets. The agreement between model calculated and observed aerosol concentrations in the industrial regions (e.g., North America and Europe) is quite similar for all three meteorological datasets. Away from the source regions, however, the comparisons with observations differ greatly for DAO, FVGCM and GISS, and the performance of the model using different datasets varies largely depending on sites and species. Global annual average aerosol optical depth at 550 nm is 0.120-0.131 for the three meteorological datasets.

Penner, Joyce E.↗

Sensitivity of Global Modeling Initiative Model Predictions of Antarctic Ozone Recovery to Input Meteorological Fields

We use the Global Modeling Initiative chemistry and transport model to simulate the evolution of stratospheric ozone between 1995 and 2030, using boundary conditions consistent with the recent World Meteorological Organization ozone assessment. We compare the Antarctic ozone recovery predictions of two simulations, one driven by an annually repeated year of meteorological data from a general circulation model (GCM), the other using a year of output from a data assimilation system (DAS), to examine the sensitivity of Antarctic ozone recovery predictions to the characteristic dynamical differences between GCM- and DAS-generated meteorological data. Although the age of air in the Antarctic lower stratosphere differs by a factor of 2 between the simulations, we find little sensitivity of the 1995-2030 Antarctic ozone recovery between 350 and 650 K to the differing meteorological fields, particularly when the recovery is specified in mixing ratio units. Percent changes are smaller in the DAS-driven simulation compared to the GCM-driven simulation because of a surplus of Antarctic ozone in the DAS-driven simulation which is not consistent with observations. The peak ozone change between 1995 and 2030 in both simulations is approx.20% lower than photochemical expectations, indicating that changes in ozone transport due to changing ozone gradients at 450 K between 1995 and 2030 constitute a small negative feedback. Total winter/spring ozone loss during the base year (1995) of both simulations and the rate of ozone loss during August and September is somewhat weaker than observed. This appears to be due to underestimates of Antarctic Cl(sub y) at the 450 K potential temperature level.

Considine, David B.↗

Future Climate Impacts of Direct Radiative Forcing Anthropogenic Aerosols, Tropospheric Ozone, and Long-lived Greenhouse Gases

Long-lived greenhouse gases (GHGs) are the most important driver of climate change over the next century. Aerosols and tropospheric ozone (O3) are expected to induce significant perturbations to the GHG-forced climate. To distinguish the equilibrium climate responses to changes in direct radiative forcing of anthropogenic aerosols, tropospheric ozone, and GHG between present day and year 2100, four 80-year equilibrium climates are simulated using a unified tropospheric chemistry-aerosol model within the Goddard Institute for Space Studies (GISS) general circulation model (GCM) 110. Concentrations of sulfate, nitrate, primary organic (POA) carbon, secondary organic (SOA) carbon, black carbon (BC) aerosols, and tropospheric ozone for present day and year 2100 are obtained a priori by coupled chemistry-aerosol GCM simulations, with emissions of aerosols, ozone, and precursors based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenario (SRES) A2. Changing anthropogenic aerosols, tropospheric ozone, and GHG from present day to year 2100 is predicted to perturb the global annual mean radiative forcing by +0.18 (considering aerosol direct effects only), +0.65, and +6.54 W m(sup -2) at the tropopause, and to induce an equilibrium global annual mean surface temperature change of +0.14, +0.32, and +5.31 K, respectively, with the largest temperature response occurring at northern high latitudes. Anthropogenic aerosols, through their direct effect, are predicted to alter the Hadley circulation owing to an increasing interhemispheric temperature gradient, leading to changes in tropical precipitation. When changes in both aerosols and tropospheric ozone are considered, the predicted patterns of change in global circulation and the hydrological cycle are similar to those induced by aerosols alone. GHG-induced climate changes, such as amplified warming over high latitudes, weakened Hadley circulation, and increasing precipitation over the Tropics and high latitudes, are consistent with predictions of a number of previous GCM studies. Finally, direct radiative forcing of anthropogenic aerosols is predicted to induce strong regional cooling over East and South Asia. Wintertime rainfall over southeastern China and the Indian subcontinent is predicted to decrease because of the increased atmospheric stability and decreased surface evaporation, while the geographic distribution of precipitation is also predicted to be altered as a result of aerosol-induced changes in wind flow.

Chen, Wei-Ting↗

A Goddard Multi-Scale Modeling System with Unified Physics

Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.

Tao, W.K.↗

The Role of Continental-scale Landmass in Monsoonal and Global Precipitation Distribution

It was argued by Chao and Chen (20011) that land-sea thermal contrast on the continental scale is not a necessary condition for monsoons and that a monsoon is an ITCZ that have moved into the subtropics in its annual cycle of latitudinal movement. Chao and Chen supported their contention by GCM experiments in which they replaced landmass by ocean and were able to generate monsoons. However, land-sea thermal contrast does exist and must play a role in monsoonal rainfall distribution. Land-sea thermal contrast is one facet of continental-scale landmass. in this article the roles of land-sea thermal contrast in monsoonal rainfall distribution and in middle latitude storm tracks are examined through GCM experiments. Comparison of a set of two GCM experiments in which the sea surface temperature (SST) from observations is prescribed from observations with and without a six-month delay reveals the role of land-sea thermal contrast. These experiments confirm that land-sea thermal contrast is not a necessary condition for monsoons and that a monsoon should be viewed as an ITCZ displaced into the subtropics, instead of a continent-sized giant sea breeze. However, land-sea thermal contrast does have influence on the distribution of monsoonal rainfall. The temperature rise over south Asia as the season moves into summer helps the Asian monsoon to start early. However, this role is not the same as that of the land-sea thermal contrast as in the conventional explanation for the cause of monsoon. The heated Landmass in summer contributes to the displacement of 1TCZ into the subtropics Also, the heated landmass in summer, by drawing moisture toward itself, limits the range of the summer storm tracks in the middle latitude oceans. On the other band, in winter the landmass does not present a competition for rainfall and thus allow middle latitude storm tracks to expand over the ocean.

Chao, Winston C.↗

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Crosson, William L↗

Global Distribution of Cloud Droplet Number Concentration, Autoconversion Rate, and Aerosol Indirect Effect Under Diabatic Droplet Activation

This study presents a global assessment of the sensitivity of droplet number to diabatic activation (i.e., including effects from entrainment of dry air) and its first-order tendency on indirect forcing and autoconversion. Simulations were carried out with the NASA Global Modeling Initiative (GMI) atmospheric and transport model using climatological metereorological fields derived from the former NASA Data Assimilation Office (DAO), the NASA Finite volume GCM (FVGCM) and the Goddard Institute for Space Studies version II (GISS) GCM. Cloud droplet number concentration (CDNC) is calculated using a physically based prognostic parameterization that explicitly includes entrainment effects on droplet formation. Diabatic activation results in lower CDNC, compared to adiabatic treatment of the process. The largest decrease in CDNC (by up to 75 percent) was found in the tropics and in zones of moderate CCN concentration. This leads to a global mean effective radius increase between 0.2-0.5 micrometers (up to 3.5 micrometers over the tropics), a global mean autoconversion rate increase by a factor of 1.1 to 1.7 (up to a factor of 4 in the tropics), and a 0.2-0.4 W m(exp -2) decrease in indirect forcing. The spatial patterns of entrainment effects on droplet activation tend to reduce biases in effective radius (particularly in the tropics) when compared to satellite retrievals. Considering the diabatic nature of ambient clouds, entrainment effects on CDNC need to be considered in GCM studies of the aerosol indirect effect.

Barahona, Donifan↗

Simulation of the Intraseasonal Variability over the Eastern Pacific ITCZ in Climate Models

During boreal summer, convective activity over the eastern Pacific (EPAC) inter-tropical convergence zone (ITCZ) exhibits vigorous intraseasonal variability (ISV). Previous observational studies identified two dominant ISV modes over the EPAC, i.e., a 40-day mode and a quasi-biweekly mode (QBM). The 40-day ISV mode is generally considered a local expression of the Madden-Julian Oscillation. However, in addition to the eastward propagation, northward propagation of the 40-day mode is also evident. The QBM mode bears a smaller spatial scale than the 40-day mode, and is largely characterized by northward propagation. While the ISV over the EPAC exerts significant influences on regional climate/weather systems, investigation of contemporary model capabilities in representing these ISV modes over the EPAC is limited. In this study, the model fidelity in representing these two dominant ISV modes over the EPAC is assessed by analyzing six atmospheric and three coupled general circulation models (GCMs), including one super-parameterized GCM (SPCAM) and one recently developed high-resolution GCM (GFDL HIRAM) with horizontal resolution of about 50 km. While it remains challenging for GCMs to faithfully represent these two ISV modes including their amplitude, evolution patterns, and periodicities, encouraging simulations are also noted. In general, SPCAM and HIRAM exhibit relatively superior skill in representing the two ISV modes over the EPAC. While the advantage of SPCAM is achieved through explicit representation of the cumulus process by the embedded 2-D cloud resolving models, the improved representation in HIRAM could be ascribed to the employment of a strongly entraining plume cumulus scheme, which inhibits the deep convection, and thus effectively enhances the stratiform rainfall. The sensitivity tests based on HIRAM also suggest that fine horizontal resolution could also be conducive to realistically capture the ISV over the EPAC, particularly for the QBM mode. Further analysis illustrates that the observed 40-day ISV mode over the EPAC is closely linked to the eastward propagating ISV signals from the Indian Ocean/Western Pacific, which is in agreement with the general impression that the 40-day ISV mode over the EPAC could be a local expression of the global Madden-Julian Oscillation (MJO). In contrast, the convective signals associated with the 40-day mode over the EPAC in most of the GCM simulations tend to originate between 150degE and 150degW, suggesting the 40-day ISV mode over the EPAC might be sustained without the forcing by the eastward propagating MJO. Further investigation is warranted towards improved understanding of the origin of the ISV over the EPAC.

Intraseasonal Variability↗

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Quattrochi, Dale A.↗