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Handling qualities, electronic flight control system configurations, and integrated digital avionics for SST automated all weather landing
Baseline instrument landing system for low visibility approach and landing of supersonic transports
This paper explores the sensitivity of Atmospheric General Circulation Model (AGCM) simulations to changes in the meridional distribution of sea surface temperature (SST). The simulations are for an aqua-planet, a water covered Earth with no land, orography or sea- ice and with specified zonally symmetric SST. Simulations from 14 AGCMs developed for Numerical Weather Prediction and climate applications are compared. Four experiments are performed to study the sensitivity to the meridional SST profile. These profiles range from one in which the SST gradient continues to the equator to one which is flat approaching the equator, all with the same maximum SST at the equator. The zonal mean circulation of all models shows strong sensitivity to latitudinal distribution of SST. The Hadley circulation weakens and shifts poleward as the SST profile flattens in the tropics. One question of interest is the formation of a double versus a single ITCZ. There is a large variation between models of the strength of the ITCZ and where in the SST experiment sequence they transition from a single to double ITCZ. The SST profiles are defined such that as the equatorial SST gradient flattens, the maximum gradient increases and moves poleward. This leads to a weakening of the mid-latitude jet accompanied by a poleward shift of the jet core. Also considered are tropical wave activity and tropical precipitation frequency distributions. The details of each vary greatly between models, both with a given SST and in the response to the change in SST. One additional experiment is included to examine the sensitivity to an off-equatorial SST maximum. The upward branch of the Hadley circulation follows the SST maximum off the equator. The models that form a single precipitation maximum when the maximum SST is on the equator shift the precipitation maximum off equator and keep it centered over the SST maximum. Those that form a double with minimum on the equatorial maximum SST shift the double structure off the equator, keeping the minimum over the maximum SST. In both situations only modest changes appear in the shifted profile of zonal average precipitation. When the upward branch of the Hadley circulation moves into the hemisphere with SST maximum, the zonal average zonal, meridional and vertical winds all indicate that the Hadley cell in the other hemisphere dominates.
Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.
Past studies have shown that the use of coarse resolution SST products such as from the real-time global (RTG) SST analysis[1] or other coarse resolution once-a-day products do not properly portray the diurnal variability of fluxes of heat and moisture from the ocean that drive the formation of low level clouds and precipitation over the ocean. For example, the use of high resolution MODIS SST composite [2] to initialize the Advanced Research Weather Research and Forecast (WRF) (ARW) [3] has been shown to improve the prediction of sensible weather parameters in coastal regions [4][5}. In an extend study, [6] compared the MODIS SST composite product to the RTG SST analysis and evaluated forecast differences for a 6 month period from March through August 2007 over the Florida coastal regions. In a comparison to buoy data, they found that that the MODIS SST composites reduced the bias and standard deviation over that of the RTG data. These improvements led to significant changes in the initial and forecasted heat fluxes and the resulting surface temperature fields, wind patterns, and cloud distributions. They also showed that the MODIS composite SST product, produced for the Terra and Aqua satellite overpass times, captured a component of the diurnal cycle in SSTs not represented in the RTG or other one-a-day SST analyses. Failure to properly incorporate these effects in the WRF initialization cycle led to temperature biases in the resulting short term forecasts. The forecast impact was limited in some situations however, due to composite product inaccuracies brought about by data latency during periods of long-term cloud cover. This paper focuses on the forecast impact of an enhanced MODIS/AMSR-E composite SST product designed to reduce inaccuracies due data latency in the MODIS only composite product.
It is well known that the sea surface temperature (SST) exhibits a diurnal cycle. Since January 2017, the NASA GMAO's Weather Analysis & Prediction System (https://gmao.gsfc.nasa.gov/weather_prediction/) includes a model for this diurnal cycle, a cool-skin layer and assimilates for skin SST. Data assimilation for the skin SST is carried out along with the 3-D state of the atmosphere, primarily using infrared radiance measurements, that are sensitive to the cool-skin and diurnal warming. In the context of Numerical Weather Prediction (NWP), this implies that the skin SST from our system is tightly coupled to the overlaying atmosphere and constrained by all the available atmospheric and surface-sensitive observations (in situ and satellite brightness temperatures). Comparisons of the SST diurnal cycle with other SST retrievals (SEVIRI (Spinning Enhanced Visible & InfraRed Imager) and AMSR-2 (Advanced Microwave Scanning Radiometer-2)) has shown mostly similar diurnal variation, however, the former decays at a faster rate. This poster presents our SST plus atmosphere assimilation methodology, and recent improvements to the skin SST model to address the known issues. Global, hourly estimates of the cool-skin and diurnal warm layer fields would be of interest to the SST retrieval community.
Recent studies have shown that, in response to a surface warming, the marine tropical low-cloud cover (LCC) as observed by passive-sensor satellites substantially decreases, therefore generating a smaller negative value of the top-of-the-atmosphere (TOA) cloud radiative effect (CRE). Here we study the LCC and CRE interannual changes in response to sea surface temperature (SST) forcings in the GISS model E2 climate model, a developmental version of the GISS model E3 climate model, and in 12 other climate models, as a function of their ability to represent the vertical structure of the cloud response to SST change against 10 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) observations. The more realistic models (those that satisfy the observational constraint) capture the observed interannual LCC change quite well ([delta]LCC]/[delta]SST= -3.49±1.01%K [negative 1 superscript] vs. [delta]LCC/[delta]SST[subscript obs]= -3.59±0.28%K[negative 1 superscript]) while the others largely underestimate it ([delta]LCC/[delta]SST= -1.32±1.28%K[negative 1 superscript]). Consequently, the more realistic models simulate more positive shortwave (SW) feedback ([delta]CRE/[delta]SST=2.60±1.13Wm[negative 2 superscript] K[negative 1 superscript]) than the less realistic models (CRE/SST=0.87±2.63Wm2K1), in better agreement with the observations ([delta]CRE/[delta]SST[subscript obs]=3±0.26Wm[negative 2 superscript] K[negative 1 superscript] ), although slightly underestimated. The ability of the models to represent moist processes within the planetary boundary layer (PBL) and produce persistent stratocumulus (Sc) decks appears crucial to replicating the observed relationship between clouds, radiation and surface temperature. This relationship is different depending on the type of low clouds in the observations. Over stratocumulus regions, cloud-top height increases slightly with SST, accompanied by a large decrease in cloud fraction, whereas over trade cumulus (Cu) regions, cloud fraction decreases everywhere, to a smaller extent.
The USCLI VAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. Specific questions that the runs are designed to address include: What are the mechanisms that maintain drought across the seasonal cycle and from one year to the next? What is the role of the leading patterns of SST variability, and what are the physical mechanisms linking the remote SST forcing to regional drought, including the role of land-atmosphere coupling? The runs were carried out with five different atmospheric general circulation models (AGCM5), and one coupled atmosphere-ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino/Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic Multi-decadal Oscillation (AMO), and a global trend pattern. One of the key findings is that all the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the U.S. tends to occur when the two oceans have anomalies of opposite sign. That is, a cold Pacific and warm Atlantic tend to produce the largest precipitation reductions, whereas a warm Pacific and cold Atlantic tend to produce the greatest precipitation enhancements. Further analysis of the response over the U.S. to the Pacific forcing highlights a number of noteworthy and to some extent unexpected results. These include a seasonal dependence of the precipitation response that is characterized by signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. Another interesting result concerns what appears to be a substantially different character in the surface temperature response over the U.S. to the Pacific forcing by the only model examined here that was developed for use in numerical weather prediction. The response to the positive SST trend forcing pattern is an overall surface warming over the world's land areas with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all the models.
Most operational centers are developing coupled (atmosphere-ocean) data assimilation systems as an alternative to uncoupled counterparts (atmosphere- or ocean-only). The Sea Surface Temperature (SST) is one of the key variables that tightly connects the atmosphere and ocean states and also air-sea fluxes. However, current prototype coupled data assimilation systems rely on external (L4) gridded SST or along-track (L3 or L2) SST retrievals as observed data or relaxation field. But in reality, SST are measurements are available from sparse in-situ network of ships, moorings, and buoys; all of them combined together are far less than those from satellites. However, satellites do not directly measure temperature, and inferring SST from satellite measured radiances requires a radiative transfer model, its calibration and also bias correction.The NASA Global Modeling and Assimilation Office (GMAO) is developing a coupled data assimilation system which assimilates SST directly from the raw observations, i.e., satellite radiances and in-situ observations. The methodology to directly assimilate radiances for SST became operational in Jan, 2017 in the GMAO's near-real time Weather Analysis and Prediction System. There were many modifications to the GMAO system in order to implement SST assimilation, most of which generally improved the predictability of the system. In order to maintain and further improve this system, we advocate for the availability of a microwave satellite radiometer in future beyond the currently operational GPM- GMI and AMSR-2 missions. For improved modeling of the near-surface temperature, salinity and mixing processes, we suggest adding more than one temperature sensor and salinity sensors to the drifting buoy network.
In this study, we perform experiments with a coupled atmosphere-ocean general circulation model (CGCM) to examine ENSO's influence on the interannual sea surface temperature (SST) variability of the tropical Indian Ocean. The control experiment includes both the Indian and Pacific Oceans in the ocean model component of the CGCM (the Indo-Pacific Run). The anomaly experiment excludes ENSOs influence by including only the Indian Ocean while prescribing monthly-varying climatological SSTs for the Pacific Ocean (the Indian-Ocean Run). In the Indo-Pacific Run, an oscillatory mode of the Indian Ocean SST variability is identified by a multi-channel singular spectral analysis (MSSA). The oscillatory mode comprises two patterns that can be identified with the Indian Ocean Zonal Mode (IOZM) and a basin-wide warming/cooling mode respectively. In the model, the IOZM peaks about 3-5 months after ENSO reaches its maximum intensity. The basin mode peaks 8 months after the IOZM. The timing and associated SST patterns suggests that the IOZM is related to ENSO, and the basin- wide warming/cooling develops as a result of the decay of the IOZM spreading SST anomalies from western Indian Ocean to the eastern Indian Ocean. In contrast, in the Indian-Ocean Run, no oscillatory modes can be identified by the MSSA, even though the Indian Ocean SST variability is characterized by east-west SST contrast patterns similar to the IOZM. In both control and anomaly runs, IOZM-like SST variability appears to be associated with forcings from fluctuations of the Indian monsoon. Our modeling results suggest that the oscillatory feature of the IOZM is primarily forced by ENSO.
A statistical-stochastic model of the complete life cycle of North Atlantic (NA) tropical cyclones (TCs) is used to examine the relationship between climate and landfall rates along the North American Atlantic and Gulf Coasts. The model draws on archived data of TCs throughout the North Atlantic to estimate landfall rates at high geographic resolution as a function of the ENSO state and one of two different measures of sea surface temperature (SST): 1) SST averaged over the NA subtropics and the hurricane season and 2) this SST relative to the seasonal global subtropical mean SST (termed relSST). Here, the authors focus on SST by holding ENSO to a neutral state. Jackknife uncertainty tests are employed to test the significance of SST and relSST landfall relationships. There are more TC and major hurricane landfalls overall in warm years than cold, using either SST or relSST, primarily due to a basinwide increase in the number of storms. The signal along the coast, however, is complex. Some regions have large and significant sensitivity (e.g., an approximate doubling of annual major hurricane landfall probability on Texas from -2 to +2 standard deviations in relSST), while other regions have no significant sensitivity (e.g., the U.S. mid-Atlantic and Northeast coasts). This geographic structure is due to both shifts in the regions of primary TC genesis and shifts in TC propagation.
Teams from the NASA Ames Research Centers (ARC) and Langley Research Center (LaRC) have been working on validating their computational fluid dynamics (CFD) results for the Boeing Mach 0.80 Transonic Truss-Braced Wing (TTBW) configuration. Experimental data used for the validation were gathered from a test conducted of a 4.5% scale Mach 0.80 TTBW model in the NASA Ames Research Center 11-by 11-Foot Transonic Wind Tunnel. The CFD simulations were initially run with both LAVA and USM3D Mixed Element solvers utilizing the Spalart-Allmaras (SA) turbulence model. A discrepancy was observed between CFD and experimental loads and moments ranging on average from 0.047 to 0.063 for lift coefficient, 16.5 to 27 in drag counts, and -0.02 to -0.032 for pitching moment, varying with the solver used. With introducing the refactored version of LAVA these values dropped to 0.034 to 0.047 for lift coefficient, 7.74 to 16.5 in drag counts, and lastly -0.012 to -0.02 for pitching moment. Based on findings from Boeing, who observed an improved comparison to experimental data when using the k-ω Shear Stress Transport (SST) turbulence model, the NASA teams conducted simulations with SST to investigate turbulence modeling sensitivities. OVERFLOW and USM3D V6 solvers were used for the comparison of SST and SA simulations. CFD results using the SST turbulence model demonstrate an improvement in matching with experimental CL values, reducing the discrepancies seen by 0.021-0.055 (62-93% reduction in discrepancy respective to the OVERFLOW and USM3D V6). The SST model has varying effects on CD, based on the solver / grid paradigm; for USM3D this prediction is only improved at higher angles of attack (above the cruise design point) resulting in a reduced discrepancy of 8.8–25 drag counts However, at the mid-to-low angles of attack, SST increases the CD discrepancy by 4-55 counts, increasing at lower angles of attack. For OVERFLOW this discrepancy only exists at the low angles of attack and maxes out at 10 counts of drag. Above α = 1.5° OVERFLOW SST reduces discrepancy by 9.3 drag counts on average.
In this paper, we have identified three principal modes of summertime rainfall variability over China and global sea surface temperature (SST) for the period 1955-1998. Using these modes, we have assessed the impact of the El Nino/La Nina on major drought and flood occurrence over China during 1997-1998. The first mode can be identified with the growth phase of El Nino superimposed on a linear warming trend since the mid-1950s. This mode strongly influences rainfall over northern China. The second mode comprises of a quasi-biennial tendency manifested in alternate wet and dry years over the Yangtze River Valley (YRV) of central China. The third mode is dominated by a quasi-decadal oscillation in eastern China between the Yangtze River and the Yellow River. Using a mode-by-mode reconstruction, we evaluate the impacts of the various principal modes on the 1997 and 1998 observed rainfall anomaly. We find that the severe drought in northern China, and to a lesser degree the flood in southern China, in 1997 is likely a result of the influence of anomalous SST forcing during the growth phase of the El Nino. In addition, rainfall in southern China may be influenced by the decadal or long-term SST variability. The severe flood over the Yangtze River Valley in 1998 is associated with the biennial tendency of basin scale SST during the transition from El Nino to La Nina in 1997-98. Additionally, the observed prolonged drought over northern China and increasing flooding over the YRV since the 1950s may be associated with a long-term warming trend in the tropical Indian and western Pacific ocean. During 1997, the El Nino SST exacerbated the drought situation over northern China. In 1998, the drought appeared to get temporary relief from the La Nina anomalous SST forcing.
In this study, we examined global zonal/annual mean precipitation trends. Land precipitation trend from 1951 to 2002 shows widespread drying between 10 S to 20 N but the trend from 1977 to 2002 shows partial recovery. Based on general circulation model sensitivity studies, we suggested that these features are driven largely by the meridional SST gradient trend in the tropics. Our idealized CCM3 experiments substantiated that land precipitation is more sensitive to meridional SST gradient than to an overall tropical warming. Various simulations produced for the IPCC 4th assessment report demonstrate that increasing CO2 increases SST in the entire tropics non-uniformly and increases land precipitation only in certain latitude belts, again pointing to the importance of SST gradient change. Temporally varying aerosols in the IPCC simulations alter meridional SST gradient and land precipitation substantially. Anthropogenic aerosol direct solar forcing without its effects on SST is shown by the CCM3 to have weak but non-negligible influence on land precipitation.
The relationships of upper tropospheric water vapor (UTWV), cloud ice and sea surface temperature (SST) are examined in the annual cycles of ECMWF analyses and simulations from 15 atmosphere-ocean coupled models which were contributed to the IPCC AR4. The results are compared with the observed relationships based on UTWV and cloud ice measurements from MLS on Aura. It is shown that the ECMWF analyses produce positive correlations between UTWV, cloud ice and SST, similar to the MLS data. The rate of the increase of cloud ice and UTWV with SST is about 30% larger than that for MLS. For the IPCC simulations, the relationships between UTWV, cloud ice and SST are qualitatively captured. However, the magnitudes of the simulated cloud ice show a considerable disagreement between models, by nearly a factor of 10. The amplitudes of the approximate linear relations between UTWV, cloud ice and SST vary by a factor up to 4.
This study compares the extreme heat and drought that developed over the United States in 2011 and 2012 with a focus on the role of SST forcing. Experiments with the NASA GEOS-5 atmospheric general circulation model show that the winter/spring response over the U.S. to the Pacific SST is remarkably similar for the two years despite substantial differences in the tropical Pacific SST. As such, the pronounced winter and early spring temperature differences between the two years (warmth confined to the south in 2011 and covering much of the continent in 2012) primarily reflect differences in the contributions from the Atlantic and Indian Oceans, with both acting to cool the east and upper mid-west during 2011, while during 2012 the Indian Ocean reinforced the Pacific-driven continental-wide warming and the Atlantic played a less important role. During late spring and summer of 2011 the tropical Pacific SST force a continued warming and drying over the southern U.S., though considerably weaker than observed. Nevertheless, the observed anomalies fall within the models intra-ensemble spread. In contrast, the rapid development of intense heat and drying over the central U.S. during June and July of 2012 falls outside the models intra-ensemble spread. The response to the SST (a northward expansion of a modest summer warming linked to the Atlantic) gives little indication that 2012 would produce record-breaking precipitation deficits and heat in the central Great Plains. A diagnosis of the 2012 observed circulation anomalies shows that the most extreme heat and drought was tied to the development of a stationary Rossby wave and an associated anomalous upper tropospheric high maintained by weather transients.
In the generally stably stratified lower stratosphere, SST exhaust plumes could spend a significant length of time in a relatively undispersed state. This effort has utilized invariant modeling techniques to simulate the separate and combined effects of atmospheric turbulence, turbulent diffusion, and chemical reactions of SST exhaust materials in the lower stratosphere. The primary results to date are: (1) The combination of relatively slow diffusive mixing and rapid chemical reactions during the Phase III wake period minimizes the effect of SST exhausts on O3 depletion by the so-called NOx catalytic cycle. While the SST-produced NO is substantially above background concentrations, it appears diffusive mixing of NO and O3 is simply too slow to produce the O3 depletions originally proposed. (2) The time required to dilute the SST exhaust plume may be a significant fraction of the total time these materials are resident in the lower stratosphere. If this is the case, then prior estimates of the environmental impact of these materials must be revised significantly downward.
A series of simulations of the late spring and early summer of 1988 were conducted in order to study the relative importance of different boundary forcings to the Goddard Laboratory for Atmospheres (GLA) model's simulation of the heat wave and drought over the Great Plains of the United States during this time period. Separate 60-day simulations were generated from 10, 20, and 30 May 1988 with a variety of boundary condition datasets. For the control experiment, climatological boundary conditions were used. This was followed by experiments in which either the observed 1988 sea surface temperatures (SST) or derived 1988 soil moisture values, or both, were used in place of the climatological fields. Additional experiments were conducted in which only tropical or midlatitude SST anomalies were used. The impact of the different boundary forcings was evaluated relative to the control simulations of the precipitation and surface air temperature over the Great Plains. It was found that the tropical SST anomalies had a significant effect in reducing precipitation in this area, while the midlatitude anomalies did not. Due to the prescribed climatological soil moistures for the SST experiments, a significant increase in surface temperature did not occur in these simulations. In contrast, the simulations with the anomalous 1988 soil moistures produced both a larger reduction of precipitation and a significant increase in surface temperature over the Great Plains. The simulations with both anomalous SST and soil moisture showed only a slight augmentation of the heat wave and drought relative to the experiments with anomalous soil moisture alone.