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At least 451 records · Page 25

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NASA NTRS2022

Impact of Biomass Burning and Stratospheric Intrusions in the Remote South Pacific Ocean Troposphere

The ozone mixing ratio spatiotemporal variability in the pristine South Pacific Ocean is studied, for the first time, using 21-year-long ozone (O3) records from the entire southern tropical and subtropical Pacific between 1994 and 2014. The analysis considered regional O3 vertical observations from ozonesondes, surface carbon monoxide (CO) observations from flasks, and three-dimensional chemistry-transport model simulations of the global troposphere. Two 21-year-long numerical simulations, with and without biomass burning emissions, were performed to disentangle the importance of biomass burning relative to stratospheric intrusions for ambient ozone levels in the region. Tagged tracers of O3 from the stratosphere and CO from various biomass burning regions have been used to track the impact of these different regions on the southern tropical Pacific O3 and CO levels. Patterns have been analyzed based on atmospheric dynamics variability. Considering the interannual variability in the observations, the model can capture the observed ozone gradients in the troposphere with a positive bias of 7.5 % in the upper troposphere/lower stratosphere (UTLS) as well as near the surface. Remarkably, even the most pristine region of the global ocean is affected by distant biomass burning emissions by convective outflow through the mid and high troposphere and subsequent subsidence over the pristine oceanic region. Therefore, the biomass burning contribution to tropospheric CO levels maximizes in the UTLS. The Southeast Asian open fires have been identified as the major contributing source to CO from biomass burning in the tropical South Pacific, contributing on average for the study period about 8.5 and 13 ppbv of CO at Rapa Nui and Samoa, respectively, at an altitude of around 12 km during the burning season in the spring of the Southern Hemisphere. South America is the second-most important biomass burning source region that influences the study area. Its impact maximizes in the lower troposphere (6.5 ppbv for Rapa Nui and 3.8 ppbv for Samoa). All biomass burning sources contribute about 15–23 ppbv of CO at Rapa Nui and Samoa and account for about 25 % of the total CO in the entire troposphere of the tropical and subtropical South Pacific. This impact is also seen on tropospheric O3, to which biomass burning O3 precursor emissions contribute only a few ppbv during the burning period, while the stratosphere–troposphere exchange is the most important source of O3 for the mid troposphere of the South Pacific Ocean, contributing about 15–20 ppbv in the subtropics.

Tropospheric ozone↗

DOE OSTI2025

Large‐Scale Statistically Meaningful Patterns (LSMPs) Associated With Precipitation Extremes Over Northern California

Abstract We analyze large‐scale statistically meaningful patterns (LSMPs) that precede extreme precipitation (PEx) events over Northern California (NorCal). We find LSMPs by applying k‐means clustering to the two leading principal components of daily 500 hPa geopotential height anomalies two days before the onset, from October to March during 1948–2015. Statistical significance testing based on Monte Carlo simulations suggests a minimum of four statistically distinguished LSMP clusters. The four LSMP clusters are characterized as Northwest continental negative height anomaly, Eastward positive “Pacific‐North American Pattern (PNA),” Westward negative “PNA,” and Prominent Alaskan ridge. These four clusters, shown in multiple variables, evolve very differently and have differing links to the Arctic and tropical Pacific regions. Using binary forecast skill measures and a new copula‐based framework for predicting PEx events, we find LSMP indices that are useful predictors of NorCal PEx events, with moisture‐based variables being the best predictors of PEx events at least 6 days before the onset, and the lower atmospheric variables being better than their upper atmospheric counterparts any day in advance tested. To ensure statistical rigor, the LSMPs analyzed here (with the modified acronym) include local tests of both significance and consistency, which are not always featured in the literature on large‐scale meteorological patterns.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Flying the TRMM Satellite in a GCM

By incorporating the Tropical Rainfall Measurement Mission (TRMM) satellite orbital information into the Colorado State University General Circulation Model (CSU GCM), we are able to 'fly' a satellite in the GCM, and sample the simulated atmosphere in the same way as the TRMM sensors sample the real atmosphere. The TRMM-sampled statistics for precipitation and radiative fluxes at annual, intraseasonal, monthly-mean and seasonal-mean diurnal time scales are evaluated by comparing the satellite-sampled against fully-sampled simulated atmospheres. The sampling rates of the TRMM sensors are significantly affected by the sensors' swath widths. The TRMM Microwave Imager (TMI) and the Visible Infrared Scanner (VIRS) sample each 2.25 x 2.25 degree grid box in the Tropics and subtropics about once per day, but at a different local time every day, while the Precipitation Radar (PR) and the Clouds and the Earth's Radiant Energy System (CERES) sensor visit each grid box about once every three days and twice per day, respectively. Besides inadequate samplings resulting from sensors' swath widths, there is a large, systematic diurnal undersampling associated with TRMM's orbital geometry for grid boxes away from the Equator. When only one month of TRMM data are used, this diurnal undersampling can lead to more daytime samples relative to nighttime samples in one hemisphere, and more nighttime samples relative to daytime samples in the other hemisphere. The resulting sampling biases (3-6 W m(exp-2)) are very pronounced in outgoing longwave radiation (OLR) over the subtropical land masses. The sampling errors in OLR monthly- and seasonal-means are less than 8 W m(exp-2) (5%) for each 2.25 x 2.25 degree grid box. The OLR monthly- and seasonal-means are not sensitive to diurnal undersamplings associated with the TRMM orbits and sensors' swath widths. However, this is not the case for total precipitation. Diurnal undersampling could produce errors as large as 20% in the Tropics and 40% in the subtropics, for the zonally averaged monthly-mean rain rates. The TRMM orbits sample each 2.25 x 2.25 degree grid box in the Tropics and subtropics 1-6 times for each hour of the day within a single season. The seasonal-mean diurnal cycles of precipitation and OLR are not well sampled for any one grid box. By either accumulating the satellite data for a long enough period, or averaging the data over a large area with a relatively uniform diurnal signal, the diurnal cycles of precipitation and OLR can be satisfactorily sampled. The effects TRMM sampling errors on the inferred tropical-mean hydrologic cycle and radiative fluxes are also evaluated. There are strong spurious oscillations associated with TRMM's orbital geometry, with periods of 23 days and 3-4 months, in tropical-mean daily and monthly precipitation. While the relative fluctuations of the sampled-OLR are negligible, the relative fluctuations of the sampled precipitation have magnitudes similar to those of the observed climate variability. Caution must therefore be used when applying TRMM observations of tropical-mean precipitation to interpret climate variations at intraseasonal and interannual scales.

Lin, Xin↗

DOE OSTI2023

Diurnal cycle of precipitation over the tropics and central United States: intercomparison of general circulation models

Diurnal precipitation is a fundamental mode of variability that climate models have difficulty in accurately simulating. Here, in this work, the diurnal cycle of precipitation (DCP) in participating climate models from the Global Energy and Water Exchanges' DCP project is evaluated over the tropics and central United States. Common model biases such as excessive precipitation over the tropics, too frequent light-to-moderate rain, and the failure to capture propagating convection in the central United States still exist. Over the central United States, the issues of too weak rainfall intensity in climate runs is well improved in their hindcast runs with initial conditions from numerical weather prediction analyses. But the improvement is minimal over the central Amazon. Incorporating the role of the large-scale environment in convective triggering processes helps resolve the phase-locking issue in many models where precipitation often incorrectly peaks near noon due to maximum insolation over land. Allowing air parcels to be lifted above the boundary layer improves the simulation of nocturnal precipitation which is often associated with the propagation of mesoscale systems. Including convective memory in cumulus parameterizations acts to suppress light-to-moderate rain and promote intense rainfall; however, it also weakens the diurnal variability. Simply increasing model resolution (with cumulus parameterizations still used) cannot fully resolve the biases of low-resolution climate models in DCP. The hierarchy modeling framework from this study is useful for identifying the missing physics in models and testing new development of model convective processes over different convective regimes.

58 GEOSCIENCES↗

DOE OSTI2020

The Impacts of Horizontal Grid Spacing and Cumulus Parameterization on Subseasonal Prediction in a Global Convection-Permitting Model

Monthlong simulations targeting four Madden–Julian oscillation events made with several global model configurations are verified against observations to assess the roles of grid spacing and convective parameterization on the representation of tropical convection and midlatitude forecast skill. Specifically, the performance of a global convection-permitting model (CPM) configuration with a uniform 3-km mesh is compared to that of a global 15-km mesh with and without convective parameterization, and of a variable-resolution “channel” simulation using 3-km grid spacing only in the tropics with a scale-aware convection scheme. It is shown that global 3-km simulations produce realistic tropical precipitation statistics, except for an overall wet bias and delayed diurnal cycle. The channel simulation performs similarly, although with an unrealistically higher frequency of heavy rain. The 15-km simulations with and without cumulus schemes produce too much light and heavy tropical precipitation, respectively. Without convection parameterization, the 15-km global model produces unrealistically abundant, short-lived, and intense convection throughout the tropics. Only the global CPM configuration is able to capture eastward-propagating Madden–Julian oscillation events, and the 15-km runs favor stationary or westward-propagating convection organized at the planetary scale. The global 3-km CPM exhibits the highest extratropical forecast skill aloft and at the surface, particularly during week 3 of each hindcast. Although more cases are needed to confirm these results, this study highlights many potential benefits of using global CPMs for subseasonal forecasting. Furthermore, results show that alternatives to global convection-permitting resolution—using coarser or spatially variable resolution—feature compromises that may reduce their predictive performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1995

Tropical stratospheric water vapor measured by the microwave limb sounder (MLS)

The lower stratospheric variability of equatorial water vapor, measured by the Microwave Limb Sounder (MLS), follows an annual cycle modulated by the quasi-biennial oscillation. At levels higher in the stratosphere, water vapor measurements exhibit a semi-annual oscillatory signal with the largest amplitudes at 2.2 and 1hPa. Zonal-mean cross sections of MLS water vapor are consistent with previous satellite measurements from the limb infrared monitor of the stratosphere (LIMS) and the stratospheric Aerosol and Gas Experiment 2 (SAGE 2) instruments in that they show water vapor increasing upwards and the polewards from a well defined minimum in the tropics. The minimum values vary in height between the retrieved 46 and 22hPa pressure levels.

Carr, E. S.↗

NASA NTRS2022

Turbulent Heat Flux, Downward Longwave Radiation and Large-Scale Atmospheric Circulation Associated with the Wintertime Barents-Kara Sea Extreme Sea Ice Loss Events

We investigate wintertime extreme sea ice loss events on synoptic to subseasonal time scales over the Barents-Kara Sea, where the largest sea ice variability is located. Consistent with previous studies, extreme sea ice loss events are associated with moisture intrusions over the Barents-Kara Sea, which are driven by the large-scale atmospheric circulation. In addition to the role of downward longwave radiation associated with moisture intrusions, which is emphasized by previous studies, our analysis shows strong turbulent heat fluxes are associated with extreme sea ice melting events, with both turbulent sensible and latent heat fluxes contributing, though turbulent sensible heat fluxes dominate. Our analysis also shows that these events are connected to tropical convective anomalies. A dipole pattern of convective anomalies with enhanced convection over the Maritime Continent and suppressed convection over the central to eastern Pacific is consistently detected about 6 to 10 days prior to extreme sea ice loss events. This pattern is associated with either the Madden-Julian Oscillation (MJO) or El Niño–Southern Oscillation (ENSO). Composites show that extreme sea ice loss events are connected to tropical convection via Rossby wave propagation in the midlatitudes. However, tropical convective anomalies alone are not sufficient to trigger extreme sea ice loss events, suggesting that extratropical variability likely modulates the connection between tropical convection and extreme sea ice loss events.

Turbulent heat flux↗

NASA NTRS1990

Tropical precipitation rates during SOP-1, FGGE, estimated from heat and moisture budgets

Using the NASA Goddard Laboratory analyses collected during the first FGGE Special Observing Period, global estimates of precipitation rates were derived for the domain between 30-deg N to 30-deg S, and the results were compared to OLR patterns and to each other to evaluate their consistency and reliability. Regional averages are presented to examine the variability of rainfall rates among selected regions of the Southern Hemisphere tropics. Finally, precipitable water was computed and compared to results derived from SMMR estimates and to the precipitation patterns. Results show that the heat and moisture budget estimates of precipitation compare favorably. Vertical profiles reveal that maximum convective heating occurs in the middle troposphere. The profile of the South Pacific convergence zone region compares best with profiles obtained over the western North Pacific.

Pedigo, Catherine B.↗

DOE OSTI2021

Information Entropy as Quantifier of Potential Predictability in the Tropical Indo-Pacific Basin

Global warming is posed to modify the modes of variability that control much of the climate predictability at seasonal to interannual scales. The quantification of changes in climate predictability over any given amount of time, however, remains challenging. Here we build upon recent advances in non-linear dynamical systems theory and introduce the climate community to an information entropy quantifier based on recurrence. The entropy, or complexity of a system is associated with microstates that recur over time in the time-series that define the system, and therefore to its predictability potential. A computationally fast method to evaluate the entropy is applied to the investigation of the information entropy of sea surface temperature in the tropical Pacific and Indian Oceans, focusing on boreal fall. In this season the predictability of the basins is controlled by two regularly varying non-linear oscillations, the El Niño-Southern Oscillation and the Indian Ocean Dipole. We compute and compare the entropy in simulations from the CMIP5 catalog from the historical period and RCP8.5 scenario, and in reanalysis datasets. Discrepancies are found between the models and the reanalysis, and no robust changes in predictability can be identified in future projections. The Indian Ocean and the equatorial Pacific emerge as troublesome areas where the modeled entropy differs the most from that of the reanalysis in many models. A brief investigation of the source of the bias points to a poor representation of the ocean mean state and basins' connectivity at the Indonesian Throughflow.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A Satellite-Based Estimate of Convective Vertical Velocity and Convective Mass Flux: Global Survey and Comparison with Radar Wind Profiler Observations

Convective vertical velocity (w c ) and convective mass flux (M c ) lie at the heart of GCM cumulus parameterizations, but few observations of these critical parameters are available. In this paper, we develop and evaluate a novel, satellite-based method for estimating profiles of w c and M c . Here, comparisons with collocated ground-based radar wind profiler (RWP) observations show that satellite estimated median w c is slightly greater than the RWP estimates, but they show solid agreement when compared at the 95th percentiles (intense updrafts). RWP-derived and satellite estimated M c are broadly comparable in the lower and middle troposphere, with some differences in the upper troposphere due to differences in convective core sampling. A k-means cluster analysis of multiple years of w c data shows that convective characteristics are distinctly different among extratropical convection, tropical land convection, and tropical oceanic convection. Tropical land convection is significantly more intense and more variable than the oceanic counterpart.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Explainable deep learning for insights in El Niño and river flows

The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interannual variability in regional hydrology across the world through long-range dependence or teleconnections. Recent research has demonstrated the value of Deep Learning (DL) methods for improving ENSO prediction as well as Complex Networks (CN) for understanding teleconnections. However, gaps in predictive understanding of ENSO-driven river flows include the black box nature of DL, the use of simple ENSO indices to describe a complex phenomenon and translating DL-based ENSO predictions to river flow predictions. Here we show that eXplainable DL (XDL) methods, based on saliency maps, can extract interpretable predictive information contained in global SST and discover SST information regions and dependence structures relevant for river flows which, in tandem with climate network constructions, enable improved predictive understanding. Our results reveal additional information content in global SST beyond ENSO indices, develop understanding of how SSTs influence river flows, and generate improved river flow prediction, including uncertainty estimation. Observations, reanalysis data, and earth system model simulations are used to demonstrate the value of the XDL-CN based methods for future interannual and decadal scale climate projections.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

National CO 2 budgets (2015–2020) inferred from atmospheric CO 2 observations in support of the global stocktake

Accurate accounting of emissions and removals of CO 2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries' carbon budgets. These estimates are based on “top-down” NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-averaged dry-air mole fraction (X CO 2 ) retrievals (ACOS v10), in situ CO 2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with “bottom-up” estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015–2020) as both a global 1° x 1° gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites' (CEOS) website. Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29–4.58 Pg CO2 yr -1 (0.90–1.25 Pg C yr -1 ). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1983

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.↗

NASA NTRS1989

Moisture structure of tropical cloud systems as inferred from SSM/I

The structure of tropical cloud systems was examined using data obtained by the Special Sensor Microwave/Imager on vertically-integrated vapor, ice, and liquid water (including precipitable water) in a cloud cluster associated with a Pacific easterly wave. The cloud cluster provided a sample of the varying signatures of bulk microphysical processes in organized tropical convection. Composition techniques were used to interpret this variability and its significance in terms of the response of convection to its thermodynamic environment. The relative intensities of the ice and liquid-water signatures should provide insight on the relative contribution of stratiform vs convective rain and the characteristics of the water budgets of mesoscale convective systems.

Robertson, Franklin R.↗

NASA NTRS2003

Intercontinental Transport of Ozone from Tropical Biomass Burning

Researchers have been looking at the connection between tropical biomass burning and ozone formation and long-range transport for roughly 15 years. One can see the linkage and transport patterns from satellite though aircraft and/or balloon-sonde profiles are required to observe the fine structure (ozone transport over thousands of km often happens in thin layers). In this review, I survey the pyrogenic ozone transport in the large oceanic basins - Indian Ocean, Pacific and Atlantic. Mechanistic complexities are discussed and examples shown from satellite, aircraft and soundings, including NASA results from TOMS, the GTE experiments and the SHADOZ sounding program. Experiments referred to include SAFARI-92, TRACE-A, INDOEX, PEM-Tropics and TRACE-P. augmented by subsidence, a variable tropopause height, and lightning - even ozone pollution from the Indian Ocean has been implicated. Over the Indian Ocean, pollution interacts with convection and the monsoon cycle.

Thompson, A. M.↗

NASA NTRS2002

Sources of Tropospheric Ozone along the Asian Pacific Rim: An Analysis of Ozonesonde Observations

The sources contributing to tropospheric ozone over the Asian Pacific Rim in different seasons are quantified by analysis of Hong Kong and Japanese ozonesonde observations with a global three-dimensional (3-D) chemical transport model (GEOS-CHEM) driven by assimilated meteorological observations. Particular focus is placed on the extensive observations available from Hong Kong in 1996. In the middle-upper troposphere (MT- UT), maximum Asian pollution influence along the Pacific Rim occurs in summer, reflecting rapid convective transport of surface pollution. In the lower troposphere (LT) the season of maximum Asian pollution influence shifts to summer at midlatitudes from fall at low latitudes due to monsoonal influence. The UT ozone minimum and high variability observed over Hong Kong in winter reflects frequent tropical intrusions alternating with stratospheric intrusions. Asian biomass burning makes a major contribution to ozone at less than 32 deg.N in spring. Maximum European pollution influence (less than 5 ppbv) occurs in spring in the LT. North American pollution influence exceeds European influence in the UT-MT, reflecting the uplift from convection and the warm conveyor belts over the eastern seaboard of North America. African outflow makes a major contribution to ozone in the low-latitude MT-UT over the Pacific Rim during November- April. Lightning influence over the Pacific Rim is minimum in summer due to westward UT transport at low latitudes associated with the Tibetan anticyclone. The Asian outflow flux of ozone to the Pacific is maximum in spring and fall and includes a major contribution from Asian anthropogenic sources year-round.

Liu, Hong-Yu↗

NASA NTRS2020

El Niño Related Tropical Land Surface Water and Energy Response in MERRA-2

Though El Niño events each have distinct evolutionary character they typically provide systematic large scale forcing for warming and increased drought frequency across the tropical continents. We assess this response in the MERRA-2 reanalysis and in a ten-member model AMIP ensemble. The lagged response (3-4 months) of mean tropical land temperature to El Niño warming in the Pacific Ocean is well represented. MERRA-2 reproduces the patterns of precipitation in the tropical regions, while the AMIP ensemble reproduces some regional responses better than others. Model skill is dependent on event forcing strength and temporal proximity to the peak of the sea surface warming. A composite approach centered on maximum Niño3.4 SSTs and lag relationships to energy fluxes and transports is used to identify mechanisms supporting tropical land warming. The composite necessarily moderates weather scale variability of the individual events, while retaining the systematic features across all events. We find that that reduced continental upward motions lead to reduced cloudiness and more shortwave radiation at the surface, as well as reduced precipitation. The increased shortwave heating at the land surface, along with reduced soil moisture leads to warmer surface temperature, more sensible heating and warming of the lower troposphere. While the composite provides a broad picture of the mechanisms governing the hydrologic response to El Niño forcing, the regional and temporal response in any given event can be quite variable. The 2015-16 El Niño, one of the strongest events, demonstrates some of the forced response noted in the composite, but with shifts in the evolution that depart from the composite, demonstrating the limitations of the composite and individuality of El Niño.

Michael G Bosilovich↗

NASA NTRS2023

Explainable deep learning for insights in El Niño and river flows

SST↗