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NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗
NASA NTRS2012

Projections of Declining Surface-Water Availability for the Southwestern United States

16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1◦ by 1◦ one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P − E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.

Seager, Richard↗
NASA NTRS2020

Attribution of Chemistry-Climate Model Initiative (CCMI) Ozone Radiative Flux Bias from Satellites

The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6-μm ozone band is a fundamental quantity for understanding chemistry-climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6-μm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Inter-comparison Project (ACCMIP) simulations. The principal culprits are tropical mid and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mWm-2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mWm-2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mWm-2). We found that AM3 and CMAM have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to difference processes. Overall, the multi-model ensemble mean bias is –133±98 mWm-2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.

Aura Tropospheric Emission Spectrometer (TES) meas↗
NASA NTRS2016

The Mexican Drought Atlas: Tree-Ring Reconstructions of the Soil Moisture Balance During the Late Pre-Hispanic, Colonial, and Modern Eras

Mexico has suffered a long history and prehistory of severe sustained drought. Drought over Mexico is modulated by ocean-atmospheric variability in the Atlantic and Pacific, raising the possibility for long-range seasonal climate forecasting, which could help mediate the economic and social impacts of future dry spells. The instrumental record of Mexican climate is very limited before 1920, but tree-ring chronologies developed from old-growth forests in Mexico can provide an excellent proxy representation of the spatial pattern and intensity of past moisture regimes useful for the analysis of climate dynamics and climate impacts. The Mexican Drought Atlas (MXDA) has been developed from an extensive network of 252 climate sensitive tree-ring chronologies in and near Mexico. The MXDA reconstructions extend from 1400 CE-2012 and were calibrated with the instrumental summer (JJA) self-calibrating Palmer Drought Severity Index (scPDSI) on a 0.5deg latitude/longitude grid extending over land areas from 14 to 34degN and 75-120degW using Ensemble Point-by-Point Regression (EPPR) for the 1944-1984 period. The grid point reconstructions were validated for the period 1920-1943 against instrumental gridded scPDSI values based on the fewer weather station observations available during that interval. The MXDA provides a new spatial perspective on the historical impacts of moisture extremes over Mexico during the past 600-years, including the Aztec Drought of One Rabbit in 1454, the drought of El Ano de Hambre in 1785-1786, and the drought that preceded the Mexican Revolution of 1909-1910. The El Nino/Southern Oscillation (ENSO) is the most important ocean-atmospheric forcing of moisture variability detected with the MXDA. In fact, the reconstructions suggest that the strongest central equatorial Pacific sea surface temperature (SST) teleconnection to the soil moisture balance over North America may reside in northern Mexico. This ENSO signal has stronger and more time-stable correlations than computed for either the Atlantic Multidecadal Oscillation or Pacific Decadal Oscillation. The extended Multivariate ENSO Index is most highly correlated with reconstructed scPDSI over northern Mexico, where warm events favor moist conditions during the winter, spring, and early summer. This ENSO teleconnection to northern Mexico has been strong over the past 150 years, but it has been comparatively weak and non-stationary in the MXDA over central and southern Mexico where eastern tropical Pacific and Caribbean/tropical Atlantic SSTs seem to be more important. The ENSO teleconnection to northern Mexico is weaker in the available instrumental PDSI, but analyses based on the millennium climate simulations with the Community Earth System Model suggest that the moisture balance during the winter, spring, and early summer over northern Mexico may indeed be particularly sensitive to ENSO forcing. Nationwide drought is predicted to become more common with anthropogenic climate change, but the MXDA reconstructions indicate that intense "All Mexico" droughts have been rare over the past 600 years and their frequency does not appear to have increased substantially in recent decades.

El Nino↗
NASA NTRS2004

Starting Vortex Identified as Key to Unsteady Ejector Performance

Unsteady ejectors are currently under investigation for use in some pulse-detonation-engine-based propulsion systems. Experimental measurements made in the past, and recently at the NASA Glenn Research Center, have demonstrated that thrust augmentation can be enhanced considerably when the driver is unsteady. In ejector systems, thrust augmentation is defined as = T(sup Total)/T(sup j), where T(sup Total) is the total thrust of the combined ejector and driving jet and T(sup j) is the thrust due to the driving jet alone. There are three images in this figure, one for each of the named thrust sources. The images are color contours of measured instantaneous vorticity. Each image is an ensemble average of at least 150 phase-locked measurements. The flow is from right to left, and the shape and location of each driver is shown on the far right of each image. The emitted vortex is a clearly defined "doughnut" of highly vortical (spinning) flow. In these planar images, the vortex appears as two distorted circles, one above, and one below the axis of symmetry. Because they are spinning in the opposite direction, the two circles have vorticity of opposite sign and thus are different colors. There is also a rectangle shown in each image. Its width represents the ejector diameter that was found experimentally to yield the highest thrust augmentation. It is apparent that the optimal ejector diameter is that which just "captures" the vortex: that is, the diameter bounding the outermost edge of the vortex structure. The exact mechanism behind the enhanced performance is unclear; however, it is believed to be related to the powerful vortex emitted with each pulse of the unsteady driver. As such, particle imaging velocimetry (PIV) measurements were obtained for three unsteady drivers: a pulsejet, a resonance tube, and a speaker-driven jet. All the drivers were tested with ejectors, and all exhibited performance enhancement over similarly sized steady drivers. The characteristic starting vortices of each driver are shown in these images. The images are color contours of measured instantaneous vorticity. Each image is an ensemble average of at least 150 phase-locked measurements. The flow is from right to left. The shape and location of each driver is shown on the far right of each image. The rectangle shown in each image represents the ejector diameter that was found experimentally to yield the highest thrust augmentation. It is apparent that the optimal ejector diameter is that which just "captures" the vortex: that is, the diameter bounding the outermost edge of the vortex structure. Although not shown, it was observed that the emitted vortex spread as it traveled downstream. The spreading rate for the pulsejet is shown as the dashed lines in the top image. A tapered ejector was fabricated that matched this shape. When tested, the ejector demonstrated superior performance to all those previously tested at Glenn (which were essentially of straight, cylindrical form), achieving a remarkable thrust augmentation of 2. The measured thrust augmentation is shown as a function of ejector length. Also shown are the thrust augmentation values achieved with the straight, cylindrical ejectors of varying diameters. Here, thrust augmentation is plotted as a function of ejector length for several families of ejector diameters. It can be seen that large thrust augmentation values are indeed obtained and that they are sensitive to both ejector length and diameter, particularly the latter. Five curves are shown. Four correspond to straight ejector diameters of 2.2, 3.0, 4.0, and 6.0 in. The fifth curve corresponds to the tapered ejector contoured to bound the emitted vortex. For each curve, there are several data points corresponding to different lengths. The largest value of thrust augmentation is 2.0 for the tapered ejector and 1.81 for the straight ejectors. Regardless of their diameters, all the ejectors trend toward peak performance at a particular leng. That the cross-sectional dimensions of optimal ejectors scaled precisely with the vortex dimensions on three separate pulsed thrust sources demonstrates that the action of the vortex is responsible for the enhanced ejector performance. The result also suggests that, in the absence of a complete understanding of the entrainment and augmentation mechanisms, methods of characterizing starting vortices may be useful for correlating and predicting unsteady ejector performance.

Paxson, Daniel E.↗
NASA NTRS1994

A comparison between general circulation model simulations using two sea surface temperature datasets for January 1979

Simulations with the UCLA atmospheric general circulation model (AGCM) using two different global sea surface temperature (SST) datasets for January 1979 are compared. One of these datasets is based on Comprehensive Ocean-Atmosphere Data Set (COADS) (SSTs) at locations where there are ship reports, and climatology elsewhere; the other is derived from measurements by instruments onboard NOAA satellites. In the former dataset (COADS SST), data are concentrated along shipping routes in the Northern Hemisphere; in the latter dataset High Resolution Infrared Sounder (HIRS SST), data cover the global domain. Ensembles of five 30-day mean fields are obtained from integrations performed in the perpetual-January mode. The results are presented as anomalies, that is, departures of each ensemble mean from that produced in a control simulation with climatological SSTs. Large differences are found between the anomalies obtained using COADS and HIRS SSTs, even in the Northern Hemisphere where the datasets are most similar to each other. The internal variability of the circulation in the control simulation and the simulated atmospheric response to anomalous forcings appear to be linked in that the pattern of geopotential height anomalies obtained using COADS SSTs resembles the first empirical orthogonal function (EOF 1) in the control simulation. The corresponding pattern obtained using HIRS SSTs is substantially different and somewhat resembles EOF 2 in the sector from central North America to central Asia. To gain insight into the reasons for these results, three additional simulations are carried out with SST anomalies confined to regions where COADS SSTs are substantially warmer than HIRS SSTs. The regions correspond to warm pools in the northwest and northeast Pacific, and the northwest Atlantic. These warm pools tend to produce positive geopotential height anomalies in the northeastern part of the corresponding oceans. Both warm pools in the Pacific produce large-scale circulation anomalies with a pattern that resembles that obtained using COADS SSTs as well as EOF 1 of the control simulation; the warm pool in the Atlantic does not. These results suggest that the differences obtained with COADS SSTs and HIRS SSTs are mostly due to the differences in the datasets over the northern Pacific. There was a blocking episode near Greenland in late January 1979. Both simulations with warm SST anomalies over the northwest and northeast Pacific show a tendency toward increased incidence of North Atlantic blocking; the simulation with warm SST anomalies over the northwest Atlantic shows a tendency toward decreased incidence. These results suggest that features in both SST datasets that do not have a counterpart in the other dataset contribute signficantly to the differences between the simulated and observed fields. The results of this study imply that uncertainties in current SST distributions for the world oceans can be as important as the SST anomalies themselves in terms of their impact on the atmospheric circulation. Caution should be exercised, therefore, when linking anomalous circulation and SST patterns, especially in long-range prediction.

Ose, Tomoaki↗
NASA NTRS2010

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Putman, William M.↗
NASA NTRS2002

Measurements of Turbulence Attenuation by a Dilute Dispersion of Solid Particles in Homogeneous Isotropic Turbulence

This research addresses turbulent gas flows laden with fine solid particles at sufficiently large mass loading that strong two-way coupling occurs. By two-way coupling we mean that the particle motion is governed largely by the flow, while the particles affect the gas-phase mean flow and the turbulence properties. Our main interest is in understanding how the particles affect the turbulence. Computational techniques have been developed which can accurately predict flows carrying particles that are much smaller than the smallest scales of turbulence. Also, advanced computational techniques and burgeoning computer resources make it feasible to fully resolve very large particles moving through turbulent flows. However, flows with particle diameters of the same order as the Kolmogorov scale of the turbulence are notoriously difficult to predict. Some simple flows show strong turbulence attenuation with reductions in the turbulent kinetic energy by up to a factor of five. On the other hand, some seemingly similar flows show almost no modification. No model has been proposed that allows prediction of when the strong attenuation will occur. Unfortunately, many technological and natural two-phase flows fall into this regime, so there is a strong need for new physical understanding and modeling capability. Our objective is to study the simplest possible turbulent particle-laden flow, namely homogeneous, isotropic turbulence with a uniform dispersion of monodisperse particles. We chose such a simple flow for two reasons. First, the simplicity allows us to probe the interaction in more detail and offers analytical simplicity in interpreting the results. Secondly, this flow can be addressed by numerical simulation, and many research groups are already working on calculating the flow. Our detailed data can help guide some of these efforts. By using microgravity, we can further simplify the flow to the case of no mean velocity for either the turbulence or the particles. In fact the addition of gravity as a variable parameter may help us to better understand the physics of turbulence attenuation. The experiments are conducted in a turbulence chamber capable of producing stationary or decaying isotropic turbulence with nearly zero mean flow and Taylor microscale Reynolds numbers up to nearly 500. The chamber is a 410 mm cubic box with the corners cut off to make it approximately spherical. Synthetic jet turbulence generators are mounted in each of the eight corners of the box. Each generator consists of a loudspeaker forcing a plenum and producing a pulsed jet through a 20 mm diameter orifice. These synthetic jets are directed into ejector tubes pointing towards the chamber center. The ejector tubes increase the jet mass flow and decrease the velocity. The jets then pass through a turbulence grid. Each of the eight loudspeakers is forced with a random phase and frequency. The resulting turbulence is highly Isotropic and matches typical behavior of grid turbulence. Measurements of both phases are acquired using particle image velocimetry (PIV). The gas is seeded with approximately 1 micron diameter seeding particles while the solid phase is typically 150 micron diameter spherical glass particles. A double-pulsed YAG laser and a Kodak ES-1.0 10-bit PIV camera provide the PIV images. Custom software is used to separate the images into individual images containing either gas-phase tracers or large particles. Modern high-resolution PIV algorithms are then used to calculate the velocity field. A large set of image pairs are acquired for each case, then the results are averaged both spatially and over the ensemble of acquired images. The entire apparatus is mounted in two racks which are carried aboard NASA's KC-135 Flying Microgravity Laboratory. The rack containing the turbulence chamber, the laser head, and the camera floats freely in the airplane cabin (constrained by competent NASA personnel) to minimize g-jitter.

Eaton, John↗