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At least 541 records · Page 30

Integration of space and in situ observations to study global climate change

The use of model-based global data sets of atmospheric circulation for studying fundamental dynamical and physical processes is discussed, focusing on limitations of the available model-based data sets. Data from the Global Weather Experiment in 1979 were analyzed by two authorized level IIIb data centers in 1980 and in 1981. The analyses led to difference in data-sparse regions such as the tropics. Study areas which can be addressed by an internally-consistent long-term multivariate data set for the atmospheric circulation are considered, including mean climate, forcing for the ocean models, global hydrological cycle, atmospheric energetics, intraseasonal variability, land surface processes, and structure and variability of vertical velocity, divergence, and diabatic heating. It is concluded that the most comprehensive technique for integrating space and in situ observations to produce this type of data set would be a four-dimensional data assimilation system with a realistic physical model of the type employed in operational numerical weather prediction.

Bengtsson, L.↗

Severe weather, sea state, and selected climatologies

With the development of aerospace launch vehicles which are to be recovered by flying back to the earth's surface, additional climatic data are needed on specific landing sites. A short discussion is presented that includes tornadoes, hurricanes, tropical storms and effects of sea states.

Brown, S. C.↗

Unforced decadal fluctuations in a coupled model of the atmosphere and ocean mixed layer

Global average temperature in a 100-year control run of a model used for greenhouse gas response simulations showed low-frequency natural variability comparable in magnitude to that observed over the last 100 years. The model variability was found to be barotropic in the atmosphere, and located in the tropical strip with largest values near the equator in the Pacific. The model variations were traced to complex, low-frequency interactions between the meridional sea surface temperature gradients in the eastern equatorial Pacific, clouds at both high and low levels, and features of the tropical atmospheric circulation. The variations in these and other model parameters appear to oscillate between two limiting climate states. The physical scenario accounting for the oscillations on decadal time scales is almost certainly not found in the real world on shorter time scales due to limited resolution and the omission of key physics (e.g., equatorial ocean dynamics) in the model. The real message is that models with dynamical limitations can still produce significant long-term variability. Only a thorough physical diagnosis of such simulations and comparisons with decadal-length data sets will allow one to decide if faith in the model results is, or is not, warranted.

Barnett, T. P.↗

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗

January-february Tropospheric Climate for the Northern Hemisphere and the 11-year Solar Cycle, the QBO and the Southern Oscillation

Examined here is a recently discovered association between the 11-year solar cycle and the atmosphere that is most easily detectable when the two phases of the Quasi-biennial Oscillation (QBO) are considered individually rather than pooled. The influence of the Southern Oscillation (SO) for either of the two QBO phases is then combined with that of the solar cycle in the form of two-predictor multiple regression. The strong and well-defined relationship between the 11-year 10.7 cm solar flux cycle and the lower troposphere Northern Hemisphere January-February climate for QBO phase-stratified samples (van Loon and Labitzke 1988, Barnston and Livezey 1989) failed for the west QBO phase in 1989. Here, the opposing 1989 event is explained, at least in part, on the basis of the phase of the SO (the cold tropical Pacific SST event of 1988 to 1989). It is demonstrated that both the SO and the solar flux have moderate and quasi-independent correlations with the climate over certain regions, and where there is strong overlap they can work either in harmony or in opposition. In 1989 in North America the influences of the SO and the flux conflicted to an unprecedented extent, and the SO was the controlling influence in most regions of the continent (western Canada being one exception). The 1989 event draws attention to the smallness of the QBO phase-stratified samples and the still more serious holes in the two-dimensional sample space of flux and SO when both factors are viewed as predictors within one QBO phase.

Barnston, Anthony G.↗

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

Robertson, Franklin R.↗

Climate variability and atmospheric teleconnection from satellite observed cloud fluctuations

To investigate the low-frequency variability of the large-scale circulation over the tropics and its relationship with different regions of the globe, statistics of cloud fluctuations, as inferred from outgoing longwave radiation (OLR) are used. The data consists of seven years of global OLR in a 2.5 x 2.5-deg grid derived from NOAA polar orbiting satellite observations. The time series of area-averaged monthly deviation from the seven-year mean of OLR over an equatorial Central Pacific region is presented. It is shown that positive and negative deviations reflect local drier and wetter than normal conditions, respectively. Consideration is given to teleconnection based on the Central Pacific variations and to southern oscillation contributions.

Lau, K. M.↗

Implications of summertime marine stratocumulus on the North American climate

This study focuses on the effects of summertime stratocumulus over the eastern Pacific. This cloud is linked to the semi-permanent sub-tropical highs that dominate the low-level circulation over the Pacific and Atlantic. Subsidence on the eastern flank of these highs creates an inversion based about 800 m above sea level that caps moist air near the surface. This air overlies cool waters driven by upwelling along the coastal regions of North America. Strong surface north-westerlies mix the boundary layer enough to saturate the air just below the capping inversion. Widespread stratocumulus is thus formed. All calculations were carried out using the GENESIS general circulation model that was run at MSFC. Among the more important properties of the model is that it includes radiative forcing due to absorption of solar radiation and the emission of infrared radiation, interactive clouds (both stratocumulus and cumulus types), exchanges of heat and moisture with the lower boundary. Clouds are interactive in the sense that they impact the circulation by modifying the fields of radiative heating and turbulent fluxes of heat and moisture in the boundary layer. In turn, clouds are modified by the winds through the advection of moisture. In order to isolate the effects of mid- and high-latitude stratocumulus, two runs were made with the model: one with and the other without stratocumulus. The runs were made for a year, but with perpetual July conditions, i.e., solar forcing was fixed. The diurnal solar cycle, however, was allowed for. The sea surface temperature distribution was fixed in both runs to represent climatological July conditions. All dependent variables were represented at 12 surfaces of constant sigma = p/p(sub O), where p is pressure and p(sub O) is surface pressure. To facilitate analysis, model output was transformed to constant pressure surfaces. Structures no smaller in size than 7.5 degrees longitude and 4.5 degrees in latitude were resolved. Smaller features of the circulation were parameterized. The model thus captures synoptic- and planetary-scale circulation features.

Clark, John H. E.↗

Decreased Northern Hemisphere Precipitation from Consecutive CO 2 Doublings Is Associated with Significant AMOC Weakening

Previous studies found many climate properties such as northern hemisphere (NH) surface temperature and precipitation respond non-monotonically when CO2 is increased from 1× to 8×CO2 relative to pre-industrial levels. Here, we explore the robustness of the non-monotonicity in the NH precipitation response in 11 coupled climate models. Eight models show a decrease in NH precipitation under repeated CO2 doubling, indicating that the non-monotonic response is a common but not universal result. Although common, the critical CO2 level where the NH precipitation decrease first occurs differs widely across models, ranging from 2×CO2 to 8×CO2. These models also show a prominent weakening in the Atlantic meridional overturning circulation (AMOC) at the same critical CO2 level, with the AMOC weakening leading the precipitation decrease. The sensitivities of NH precipitation and the AMOC to CO2 doublings are positively correlated, especially when the AMOC weakens beyond 10 Sv. This suggests that the differences in models' AMOC response can explain their contrasting NH precipitation responses, where models with a large AMOC weakening have decreased NH precipitation. Regionally, this decrease in NH precipitation is the most prominent over the North Atlantic, Europe and the tropical Pacific. Our results suggest that special care must be taken with the use of pattern scaling to inform regional climate decision-making.

Atlantic meridional overturning circulation↗

How Well Does NASA GEOS Model Perform in Simulating Dust Deposition into the Tropical Atlantic Ocean?

Massive dust emitted from North Africa can transport long distances across the tropical Atlantic Ocean, reaching the Americas. Dust deposition along the transit adds microorganisms and essential nutrients to marine ecosystem, which has important implications for biogeochemical cycle and climate. However, assessing the dust-ecosystemclimate interactions has been hindered in part by the paucity of dust deposition measurements and large uncertainties associated with oversimplified representations of dust processes in current models. We have recently produced a unique dataset of seasonal dust deposition flux and dust loss frequency into the tropical Atlantic Ocean at a nominal resolution of 200 km x 500 km by using the decade-long (2007-2016) record of aerosol three-dimensional distribution from four satellite sensors, namely CALIOP, MODIS, MISR, and IASI. On the basis of the ten-year average, the yearly dust deposition into the tropical Atlantic Ocean is estimated at 98-153 Tg. The dust deposition shows large spatial and temporal (on seasonal and interannual scale) variability. The satellite observations also yield an estimate of annual mean dust loss frequency of 0.052 ~ 0.078 d-1, a useful diagnostic that makes it possible to disentangle the dust transport and removal processes from the dust emissions when identifying the major factors contributing to the uncertainties and biases in the model simulated dust deposition. In this study, we use the dataset along with in situ and remote sensing observations to assess how well NASA GEOS model performs in simulating trans-Atlantic dust transport and deposition. We found that the GEOS modeling of dust deposition falls within the range of satellite-based estimates. However, this reasonable agreement in dust deposition is a compensation of the model's underestimate of dust emissions and overestimate of dust removal efficiency. Further, the overestimate of dust removal efficiency results largely from the model's overestimate of rainfall rate. Our results provide insights into the model's deficiencies at process level, which could better guide model improvements.

Yu, Hongbin↗

Improving Global Reanalyses and Short Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a "1+1"D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the "1+1"D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+lD scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSM/I rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗

Improving Global Reanalyses and Short-Range Forecast Using TRMM and SSM/I-Derived Precipitation and Moisture Observations

Global reanalyses currently contain significant errors in the primary fields of the hydrological cycle such as precipitation, evaporation, moisture, and the related cloud fields, especially in the tropics. The Data Assimilation Office (DAO) at the NASA Goddard Space Flight Center has been exploring the use of tropical rainfall and total precipitable water (TPW) observations from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments to improve short-range forecast and reanalyses. We describe a 1+1D procedure for assimilating 6-hr averaged rainfall and TPW in the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The algorithm is based on a 6-hr time integration of a column version of the GEOS DAS, hence the 1+1D designation. The scheme minimizes the least-square differences between the observed TPW and rain rates and those produced by the column model over the 6-hr analysis window. This 1+1D scheme, in its generalization to four dimensions, is related to the standard 4D variational assimilation but uses analysis increments instead of the initial condition as the control variable. Results show that assimilating the TMI and SSW rainfall and TPW observations improves not only the precipitation and moisture fields but also key climate parameters such as clouds, the radiation, the upper-tropospheric moisture, and the large-scale circulation in the tropics. In particular, assimilating these data reduce the state-dependent systematic errors in the assimilated products. The improved analysis also provides better initial conditions for short-range forecasts, but the improvements in forecast are less than improvements in the time-averaged assimilation fields, indicating that using these data types is effective in correcting biases and other errors of the forecast model in data assimilation.

Hou, Arthur Y.↗

An 11-year Solar-Cycle in Tropospheric Ozone from TOMS Measurements

Tropospheric column ozone derived from Nimbus 7 total ozone mapping spectrometer (TOMS) footprint measurements in the tropical western Pacific for 1979-1992 provide the first observational evidence of changes in tropospheric ozone which are out of phase with the stratospheric ozone changes on a time scale of a solar cycle. The estimated changes in tropospheric and stratospheric column ozone over a solar cycle are respectively -2.97 and 8.83 DU (Dobson units) or - 12.7 and 3.7% from the solar minimum to solar maximum. These observations are qualitatively consistent with a modulation effect on tropospheric ozone photochemistry by UV-induced changes in stratospheric ozone. However, in the low NO(x) regime of the marine atmosphere, the observed changes are significantly larger than estimated from a photochemical model. The solar cycle detected in tropospheric ozone is estimated to produce approximately 0.1-0.25 W m(exp -2) anomalous radiative forcing in the tropics. The combination of this with other radiative sources may have substantial influence on both regional and global climate.

Chandra, S.↗

Spacebased Observations of Oceanic Influence on the Annual Variation of South American Water Balance

The mass change of South America (SA) continent measured by the Gravity Recovery and Climate Experiment (GRACE) imposes a constraint on the uncertainties in estimating the annual variation of rainfall measured by Tropical Rain Measuring Mission (TRMM) and ocean moisture influx derived from QuikSCAT data. The approximate balance of the mass change rate with the moisture influx less climatological river discharge, in agreement with the conservation principle, bolsters not only the credibility of the spacebased measurements, but supports the characterization of ocean's influence on the annual variation of continental water balance. The annual variation of rainfall is found to be in phase with the mass change rate in the Amazon and the La Plata basins, and the moisture advection across relevant segments of the Pacific and Atlantic coasts agrees with the annual cycle of rainfall in the two basins and the Andes mountains.

rainfall annual cycle↗

Variation of a Lightning NOx Indicator for National Climate Assessment

During the past couple of years, an analysis tool was developed by the NASA Marshall Space Flight Center (MSFC) for the National Climate Assessment (NCA) program. The tool monitors and examines changes in lightning characteristics over the conterminous US (CONUS) on a continual basis. In this study, we have expanded the capability of the tool so that it can compute a new climate assessment variable that is called the Lightning NOx Indicator (LNI). Nitrogen oxides (NOx = NO + NO2) are known to indirectly influence our climate, and lightning NOx is the most important source of NOx in the upper troposphere (particularly in the tropics). The LNI is derived using Lightning Imaging Sensor (LIS) data and is computed by summing up the product of flash area x flash brightness over all flashes that occur in a particular region and period. Therefore, it is suggested that the LNI is a proxy to lightning NOx production. Specifically, larger flash areas are consistent with longer channel length and/or more energetic channels, and hence more NOx production. Brighter flashes are consistent with more energetic channels, and hence more NOx production. The location of the flash within the thundercloud and the optical scattering characteristics of the thundercloud are of course complicating factors. We analyze LIS data for the years 2003-2013 and provide geographical plots of the time-evolution of the LNI in order to determine if there are any significant changes or trends between like seasons, or from year to year.

Koshak, William J.↗

Solar Cycle Variations in Mesospheric Carbon Monoxide

As an extension of Lee et al. (2013), solar cycle variation of carbon monoxide (CO) is analyzed with MLS observation, which covers more than thirteen years (2004-2017) including maximum of solar cycle 24. Being produced primarily by the carbon dioxide (CO2) photolysis in the lower thermosphere, the variations of the mesospheric CO concentration are largely driven by the solar cycle modulated ultraviolet (UV) variation. This solar signal extends down to the lower altitudes by the dynamical descent in the winter polar vortex, showing a time lag that is consistent with the average descent velocity. To characterize a global distribution of the solar impact, MLS CO is correlated with the SORCE measured total solar irradiance (TSI) and UV. As high as 0.8 in most of the polar mesosphere, the linear correlation coefficients between CO and UV/TSI are more robust than those found in the previous work. The photochemical contribution explains most (68%) of the total variance of CO while the dynamical contribution accounts for 21% of the total variance at upper mesosphere. The photochemistry driven CO anomaly signal is extended in the tropics by vertical mixing. The solar cycle signal in CO is further examined with the Whole Atmosphere Community Climate Model (WACCM) 3.5 simulation by implementing two different modeled Spectral Solar Irradiances (SSIs): SRPM 2012 and NRLSSI. The model simulations underestimate the mean CO amount and solar cycle variations of CO, by a factor of 3, compared to those obtained from MLS observation. Different inputs of the solar spectrum have small impacts on CO variation.

MLS↗

From the Upper Troposphere Through the Stratosphere: How Satellite Measurements Help Us Decode the Past to Better Project the Future

Decades of observations of key chemical species are allowing us to more fully understand processes important to transport and composition from the upper troposphere through the stratosphere. This talk will focus on a few examples and how they are informing our understanding of variability, trends, and future projections. The growth of the Antarctic ozone hole (late 1970s – mid 1990s) caused a dynamical perturbation to the Southern Hemisphere stratospheric circulation visible in ozone, one of our longest and best observed chemical constituents, and illustrates the connection between chemical change and the coupled radiative and dynamical response that challenges chemistry-climate models (CCMs). The quasi-biennial oscillation (QBO) is the dominant mode of interannual variability in the tropical stratosphere, however its impacts on stratospheric circulation and composition can be traced globally. The QBOs timing with respect to the seasonal cycle in each hemisphere is significant in understanding its impact on up to decadal scale variability. The El Nino Southern Oscillation (ENSO), which dominates tropical tropospheric interannual variability, also affects the stratosphere and its influence is visible in our growing record of tropospheric and stratospheric composition measurements. I will discuss how our knowledge of response has grown and how representation of these observed responses in CCMs is key both to understanding recent trends and to reducing uncertainty in future changes of composition.

Luke David Oman↗

State of Wildfires

Fire is an essential component of ecosystems and acts as key driver of biogeochemical cycling with impacts on vegetation structure and composition, soil conditions, and climate feedbacks. Fire behavior and effects vary based on the types of fuel, fuel dryness, and frequency of ignition. Due to changing climate and land use patterns, fire danger is increasing in many regions globally, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Recurrent fires help to determine the distribution of trees and grasses, and overall fuel load, which inform the behavior of future fires. Process-based models can be used to capture multi-scale impacts at the forest stand-level up to the landscape level, and across minutes to centuries, but must capture variation in fire behavior and intensity as a function of the fuel and climate, from high intensity forest crown fires within boreal regions to low intensity rapid grass fires of the tropics. Fire model development demonstrates our ability to capture large scale fire influenced biogeography and vegetation distribution at the earth system scale through vegetation traits and fire feedbacks. At the individual stand scale the importance of interactions and feedbacks between above and below ground process is essential to capturing the vegetation dynamics across boreal forest systems. Improving the mechanics of including plant physiology and specifically live fuel moisture content is the next step to advancing the capability of process based models to inform fire research. Advances in the testing and creation of a mechanistic live fuel moisture model demonstrate the foundation for future live fuel dynamics research that can be informed by field and remote sensing information. Improved remote sensing, technological and modeling capabilities support a more comprehensive and cohesive fire response that will be better equipped to overcome current barriers and anticipate the new reality of fires in a warming world.

wildfires↗