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NASA NTRS2007

Weather Research and Forecasting Model Sensitivity Comparisons for Warm Season Convective Initiation

Mesoscale weather conditions can significantly affect the space launch and landing operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). During the summer months, land-sea interactions that occur across KSC and CCAFS lead to the formation of a sea breeze, which can then spawn deep convection. These convective processes often last 60 minutes or less and pose a significant challenge to the forecasters at the National Weather Service (NWS) Spaceflight Meteorology Group (SMG). The main challenge is that a "GO" forecast for thunderstorms and precipitation at the Shuttle Landing Facility is required at the 90 minute deorbit decision for End Of Mission (EOM) and at the 30 minute Return To Launch Site (RTLS) decision. Convective initiation, timing, and mode also present a forecast challenge for the NWS in Melbourne, FL (MLB). The NWS MLB issues such tactical forecast information as Terminal Aerodrome Forecasts (TAF5), Spot Forecasts for fire weather and hazardous materials incident support, and severe/hazardous weather Watches, Warnings, and Advisories. Lastly, these forecasting challenges can also affect the 45th Weather Squadron (45 WS), which provides comprehensive weather forecasts for shuttle launch, as well as ground operations, at KSC and CCAFS. The need for accurate mesoscale model forecasts to aid in their decision making is crucial. This study specifically addresses the skill of different model configurations in forecasting warm season convective initiation. Numerous factors influence the development of convection over the Florida peninsula. These factors include sea breezes, river and lake breezes, the prevailing low-level flow, and convergent flow due to convex coastlines that enhance the sea breeze. The interaction of these processes produces the warm season convective patterns seen over the Florida peninsula. However, warm season convection remains one of the most poorly forecast meteorological parameters. To determine which configuration options are best to address this specific forecast concern, the Weather Research and Forecasting (WRF) model, which has two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM) was employed. In addition to the two dynamical cores, there are also two options for a "hot-start" initialization of the WRF model - the Local Analysis and Prediction System (LAPS; McGinley 1995) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS; Brewster 1996). Both LAPS and ADAS are 3- dimensional weather analysis systems that integrate multiple meteorological data sources into one consistent analysis over the user's domain of interest. This allows mesoscale models to benefit from the addition of highresolution data sources. Having a series of initialization options and WRF cores, as well as many options within each core, provides SMG and MLB with considerable flexibility as well as challenges. It is the goal of this study to assess the different configurations available and to determine which configuration will best predict warm season convective initiation.

Watson, Leela R.↗
NASA NTRS2012

A Technique Using Principal Component Analysis to Compare Seasonal Cycles of Earth Radiation from CERES and Model Computations

A method for quantitatively comparing the seasonal cycles of two global data sets is presented. The seasonal cycles of absorbed solar radiation (ASR) and outgoing longwave radiation (OLR) have been computed from an eight-year data set from the Clouds and Earth's Radiant Energy System (CERES) scanning radiometers and from a model data set produced by the NASA Goddard Space Flight Center Global Modeling and Assimilation Office. To compare the seasonal cycles from these two data sets, principal component (PC) analysis is used, where the PCs express the time variations and the corresponding empirical orthogonal functions (EOFs) describe the geographic variations. Ocean has a long thermal response time compared to land, so land and ocean are separated for the analysis. The root-mean square values for the seasonal cycles of ASR and OLR are extremely close for the two data sets. The first three PCs are quite close, showing that the time responses and magnitudes over the globe are very similar. The agreement between the two sets of PCs is quantified by computing the matrix of inner products of the two sets. For ASR over land, the first PCs of CERES and the model agree to better than 99.9%. The EOF maps are similar for most of the globe, but differ in a few places, and the agreement of the EOF maps is likewise quantified. Maps of differences between the annual cycles show regions of agreement and disagreement.

Smith, G. Louis↗
NASA NTRS2012

Snow Cover and Precipitation Impacts on Dry Season Streamflow in the Lower Mekong Basin

Climate change impacts on dry season streamflow in the Mekong River are relatively understudied, despite the fact that water availability during this time is critically important for agricultural and ecological systems. Analyses of two gauging stations (Vientiane and Kratie) in the Lower Mekong Basin (LMB) show significant positive correlations between dry season (March through May, MAM) discharge and upper basin snow cover and local precipitation. Using snow cover, precipitation, and upstream discharge as predictors, we develop skillful regression models for MAM streamflow at Vientiane and Kratie, and force these models with output from a suite of general circulation model (GCM) experiments for the twentieth and twenty-first centuries. The GCM simulations predict divergent trends in snow cover (decreasing) and precipitation (increasing) over the twenty-first century, driving overall negligible long-term trends in dry season streamflow. Our study demonstrates how future changes in dry season streamflow in the LMB will depend on changes in snow cover and precipitation, factors that will need to be considered when assessing the full basin response to other climatic and non-climatic drivers.

Cook, Benjamin I.↗
NASA NTRS2014

The Role of Phytoplankton Dynamics in the Seasonal and Interannual Variability of Carbon in the Subpolar North Atlantic - a Modeling Study

We developed an ecosystem/biogeochemical model system, which includes multiple phytoplankton functional groups and carbon cycle dynamics, and applied it to investigate physical-biological interactions in Icelandic waters. Satellite and in situ data were used to evaluate the model. Surface seasonal cycle amplitudes and biases of key parameters (DIC, TA, pCO2, air-sea CO2 flux, and nutrients) are significantly improved when compared to surface observations by prescribing deep water values and trends, based on available data. The seasonality of the coccolithophore and "other phytoplankton" (diatoms and dinoflagellates) blooms is in general agreement with satellite ocean color products. Nutrient supply, biomass and calcite concentrations are modulated by light and mixed layer depth seasonal cycles. Diatoms are the most abundant phytoplankton, with a large bloom in early spring and a secondary bloom in fall. The diatom bloom is followed by blooms of dinoflagellates and coccolithophores. The effect of biological changes on the seasonal variability of the surface ocean pCO2 is nearly twice the temperature effect, in agreement with previous studies. The inclusion of multiple phytoplankton functional groups in the model played a major role in the accurate representation of CO2 uptake by biology. For instance, at the peak of the bloom, the exclusion of coccolithophores causes an increase in alkalinity of up to 4 μmol kg(sup −1) with a corresponding increase in DIC of up to 16 μmol kg(sup −1). During the peak of the bloom in summer, the net effect of the absence of the coccolithophores bloom is an increase in pCO2 of more than 20 μatm and a reduction of atmospheric CO2 uptake of more than 6 mmolm(sup −2) d(sup −1). On average, the impact of coccolithophores is an increase of air-sea CO2 flux of about 27 %. Considering the areal extent of the bloom from satellite images within the Irminger and Icelandic Basins, this reduction translates into an annual mean of nearly 1500 tonnes C yr(sup −1).

Earth Resources↗
NASA NTRS2012

Characterization of Aerosols over the Indochina Peninsula from Satellite-Surface Observations During Biomass Burning Pre-Monsoon Season

This paper presents characterization of aerosols over the Indochina peninsular regions of Southeast Asia during pre-monsoon season from satellite and ground-based radiometric observations. Our analysis focuses on the seasonal peak period in aerosol loading and biomass burning, prior to the onset of the Asian summer monsoon, as observed in the inter-annual variations of Aerosol Optical Depth (AOD) and fire count data from MODIS. Multi-year (2007-2011) analysis of spaceborne lidar measurements, from CALIOP, indicates presence of aerosols mostly within boundary layer, however extending to elevated altitudes to approx. 4 km over northern regions of Indochina, encompassing Myanmar, northern Thailand and southern China. In addition, a strong gradient in aerosol loading and vertical distribution is observed from the relatively clean equatorial conditions to heavy smoke-laden northern regions (greater aerosol extinction and smaller depolarization ratio). Based on column-integrated ground-based measurements from four AERONET locations distributed over Thailand, the regional aerosol loading is found to be significantly absorbing with spectral single scattering albedo (SSA) below 0.91+/-0.02 in the 440-1020 nm range, with lowest seasonal mean SSA (most absorbing aerosol) over the northern location of Chiang Mai (SSA approx. 0.85) during pre-monsoon season. The smoke-laden aerosol loading is found to exhibit a significant diurnal pattern with higher AOD departures during early morning observations relative to late afternoon conditions (peak difference of more than 15% amplitude). Finally, satellite-based aerosol radiative impact is assessed using CERES shortwave Top-of-Atmosphere flux, in conjunction with MODIS AOD. Overall, a consistency in the aerosol-induced solar absorption characteristic is found among selected regions from ground-based sunphotometer-derived spectral SSA retrievals and satellite-based radiative forcing analysis.

Indochina↗
NASA NTRS2015

Chlorophyll Variability in the Oligotrophic Gyres: Mechanisms, Seasonality and Trends

A 16-year (1998-2013) analysis of trends and seasonal patterns was conducted for the 5 subtropical ocean gyres using chlorophyll-a (Chl-a) retrievals from ocean color satellite data, sea surface temperature (SST) obtained from optimally interpolated Advanced Very High Resolution Radiometer (AVHRR) data, and sea-level anomaly (SLA) from Aviso multi-sensor altimetry data. Trend analysis was also performed on mixed-layer data derived from gridded temperature and salinity profiles (1998-2010) from the Simple Ocean Data Assimilation (SODA) model. The Chl-a monthly composites were constructed from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) on Aqua using two different algorithms: the standard algorithm (STD) that has been in use since the start of the SeaWiFS mission in 1997, and a more recently developed Ocean Color Index (OCI) algorithm that is purported to provide improved accuracy in low chlorophyll waters such as the oligotrophic regions of the subtropical gyres. Trends were obtained for all gyres using both STD and OCI algorithms, which demonstrated generally consistent results. The North Pacific, Indian Ocean, North Atlantic and South Atlantic gyres showed significant downward trends in Chl-a, while the South Pacific gyre has a much weaker upward trend with no statistical significance. Time series of satellite-derived net primary production (NPP) showed downward trends for all the gyres, while all 5 gyres exhibited positive trends in SST and SLA. The seasonal variability of Chl-a in each gyre is tightly coupled to the variability in mixed layer depth (MLD) with peak values in winter in both hemispheres when vertical mixing is more vigorous, reaching depths approaching the nutricline (ZNO3, here defined as the depth of the 0.2 micron nitrate concentration). On a seasonal basis, Chl-a concentrations increase when the MLD approaches or is deeper than the nutricline depth, in agreement with the concept that vertical mixing is the major driving mechanism for phytoplankton photosynthesis in the interior of the gyres. In addition, MLD and SST seasonal changes are well correlated indicating that SST is a reasonable index of vertical mixing in the gyres. The combination of surface warming trends and biomass reduction over the 16-year period has the potential to reduce atmospheric CO2 uptake by the gyres and therefore influence the global carbon cycle.

Long-term trends↗
NASA NTRS2014

Investigating the Sensitivity of Surface-Level Nitrate Seasonality in Antarctica to Primary Sources Using a Global Model

Determining the sources of total nitrate (TNIT NO-3 + HNO3) reaching Antarctica is a long-standing challenge. Here we analyze the monthly sensitivity of surface-level TNIT in Antarctica to primary sources using a global 3-D chemical transport model, GEOS-Chem, and its adjoint. Modeled seasonal variation of TNIT concentrations shows good agreement with several measurement studies, given that the lack of post-depositional processing in the model leads to an expected underestimate of maximum values in November through January. Remote NOx sources have the greatest impact May-July, during when the model background concentrations are sensitive to NOx emissions from fossil fuel combustion, soil, and lightning originating from 25S to 65S. In this season, NOx is transported to Antarctica as TNIT, which is formed above continental source regions at an altitude of 5-11 km. In other seasons, more NOx is transported as a reservoir species (e.g., peroxyacetyl nitrate, PAN) through the free troposphere, transforming into TNIT within a cone of influence that extends to 35S and above 4 km altitude. Photolysis of PAN over Antarctica is the main driver of modeled NOx seasonality. Stratospheric production and loss of tracers are relatively unimportant in monthly sensitivities in GEOS-Chem, driving only a few percent of surface level variability of TNIT. A small peak concentration in August is captured by the model, although some measured values in August fall outside the range of simulated concentrations. Modifications to the model to represent sedimentation of polar stratospheric clouds (PSCs) lead to increased surface level August TNIT concentrations. However, this simple representation does not explicitly account for PSC particle deposition or disappearance of the tropopause in the middle of winter, and thus the influence of stratospheric nitrate sources estimated in this study is likely a lower bound.

stratosphere↗
NASA NTRS2015

Estimating Viscoelastic Deformation Due to Seasonal Loading

Scientists have been making summer-­‐time geodetic measurements in south central Alaska for decades to estimate the rate at which a continental-­‐ocean terrane is accreting to the North American continent. Southern Alaska has big earthquakes every century and large, rapidly changing glaciers. In the last decade, primarily as part of the EarthScope Plate Boundary Observatory project, continuous GPS measurements have recorded the response of sites such as the near-­‐coastal geodetic site, AB35 to competing processes: uplift and movement to the northwest due to tectonic forces and the response of the solid Earth to seasonal and longer-­‐term changes in the cryosphere (snow and ice) surrounding the site. Which process causes the largest displacements of the site? Figure 1 (Blewitt, Nevada Geodetic Lab, 2015) shows the Northward, Eastward, and Upward motion of AB35 between 2007 and 2015. The site is moving rapidly to the north and west reflecting the tectonic convergence of site toward interior Alaska but there is small wiggle on the North component reflecting seasonal displacements of the site associated with snow loading and unloading. However, the Up component, shows a large seasonal signal due to snow loading in the winter (down) and ice and snow melting in the warmer months (site goes up). Between 2007 and the present, the site position is slowly moving upward, due to tectonic forcing but probably associated with longer-­‐ term ice melting as well. We are using the CIG finite element modeling (FEM) program Pylith to estimate the surface displacements and stresses associated with seasonal loading changes (top figure and Figure 2 far right) for water year 2012, 2011.8 - 2012.8) and the longer-­‐term retreat of the surrounding glaciers.

Alaska↗
NASA NTRS2016

Regional Atmospheric CO2 Inversion Reveals Seasonal and Geographic Differences in Amazon Net Biome Exchange

Understanding tropical rainforest carbon exchange and its response to heat and drought is critical for quantifying the effects of climate change on tropical ecosystems, including global climate carbon feedbacks. Of particular importance for the global carbon budget is net biome exchange of CO2 with the atmosphere (NBE), which represents nonfire carbon fluxes into and out of biomass and soils. Subannual and sub-Basin Amazon NBE estimates have relied heavily on process-based biosphere models, despite lack of model agreement with plot-scale observations. We present a new analysis of airborne measurements that reveals monthly, regional-scale (Approx.1-8 x 10(exp -6) km2) NBE variations. We develop a regional atmospheric CO2 inversion that provides the first analysis of geographic and temporal variability in Amazon biosphere-atmosphere carbon exchange and that is minimally influenced by biosphere model-based first guesses of seasonal and annual mean fluxes. We find little evidence for a clear seasonal cycle in Amazon NBE but do find NBE sensitivity to aberrations from long-term mean climate. In particular, we observe increased NBE (more carbon emitted to the atmosphere) associated with heat and drought in 2010, and correlations between wet season NBE and precipitation (negative correlation) and temperature (positive correlation). In the eastern Amazon, pulses of increased NBE persisted through 2011, suggesting legacy effects of 2010 heat and drought. We also identify regional differences in postdrought NBE that appear related to long-term water availability. We examine satellite proxies and find evidence for higher gross primary productivity (GPP) during a pulse of increased carbon uptake in 2011, and lower GPP during a period of increased NBE in the 2010 dry season drought, but links between GPP and NBE changes are not conclusive. These results provide novel evidence of NBE sensitivity to short-term temperature and moisture extremes in the Amazon, where monthly and sub-Basin estimates have not been previously available.

precipitation↗
NASA NTRS2017

Early Season Large-Area Winter Crop Mapping Using MODIS NDVI Data, Growing Degree Days Information and a Gaussian Mixture Model

Knowledge on geographical location and distribution of crops at global, national and regional scales is an extremely valuable source of information applications. Traditional approaches to crop mapping using remote sensing data rely heavily on reference or ground truth data in order to train/calibrate classification models. As a rule, such models are only applicable to a single vegetation season and should be recalibrated to be applicable for other seasons. This paper addresses the problem of early season large-area winter crop mapping using Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI) time-series and growing degree days (GDD) information derived from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product. The model is based on the assumption that winter crops have developed biomass during early spring while other crops (spring and summer) have no biomass. As winter crop development is temporally and spatially non-uniform due to the presence of different agro-climatic zones, we use GDD to account for such discrepancies. A Gaussian mixture model (GMM) is applied to discriminate winter crops from other crops (spring and summer). The proposed method has the following advantages: low input data requirements, robustness, applicability to global scale application and can provide winter crop maps 1.5-2 months before harvest. The model is applied to two study regions, the State of Kansas in the US and Ukraine, and for multiple seasons (2001-2014). Validation using the US Department of Agriculture (USDA) Crop Data Layer (CDL) for Kansas and ground measurements for Ukraine shows that accuracies of greater than 90% can be achieved in mapping winter crops 1.5-2 months before harvest. Results also show good correspondence to official statistics with average coefficients of determination R(exp. 2) greater than 0.85.

mixture model↗
NASA NTRS2018

Characterizing Differences in the Aerosol Plume and Cloud Structure over Ascension Island During the 2016 and 2017 Biomass Burning Seasons

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Through the use of AMF1 observations, the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and back trajectories from the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT), it will be demonstrated that differences in the atmospheric circulation during the two years result in varying aerosol conditions over Ascension Island. When the aerosol plume is overhead, the aerosol loading is higher during the 2016 season as a result of a weaker subtropical high-pressure system. Furthermore, the aerosol plume originates from central Africa in 2016, but further south in 2017. Contrasts in the season-to-season and day-to-day aerosol loading are used to categorize boundary layer cloud and sub-cloud turbulence measurements above Ascension Island using the AMF1 Doppler lidar and cloud radar.

Collow, Allison B. Marquardt↗
NASA NTRS2019

Seasonal Variation in Martian Water Ice Cloud Particle Size

We employ the complete record of Mars limb-viewing observations by the Compact Reconnaissance Imaging Spectrometer, totaling 922 successful retrievals, to chart the seasonal variation in water ice cloud particle size. Low-latitude clouds exhibit particle size sorting with altitude at all seasons, with particles ranging from >3.0 m in effective radius to 1.01.5 m. However, at a given altitude, the ice particle size often varies through the year. Ice particle sizes in the tropics follow a different seasonal cycle than ice mixing ratio. North polar clouds have a complex seasonal cycle, with a sloped size profile with altitude as the polar hood cloud forms in early fall trending to a roughly uniform 1.5 m profile by the end of winter. These data are an important metric to validate and improve general circulation model microphysical routines and to better understand how martian water ice clouds influence the atmospheric radiative budget.

Scott D. Guzewich↗
NASA NTRS2019

Seasonal Dependence of SMAP Radiometer-Based Soil Moisture Performance as Observed over Core Validation Sites

The NASA SMAP (Soil Moisture Active Passive) mission provides a global coverage of soil moisture measurements based on its L-band microwave radiometer every 2-3 days at about 40 km resolution. The soil moisture retrieval algorithms model the brightness temperature as a function of soil moisture, surface conditions and vegetation. External data sources inform the algorithms about the surface conditions and vegetation, which enable the retrieval of soil moisture. The inversion process contains uncertainties related to radiometer measurements, forward model assumptions and ancillary data sources. This study focuses on the uncertainties that depend on the seasonal evolution of the surface conditions and vegetation. This study compares the SMAP and core validation site (CVS) soil moisture values over a period of three years to extract the evolution of performance metrics over time. The analysis showed that most CVS that include managed agriculture exhibit significant time-dependent seasonal bias. This bias was linked to seasonal temperature cycle, which is a proxy to several features that can cause seasonally dependent errors in the SMAP product.

core validation site↗
NASA NTRS2019

Seasonal Variations in Atmospheric Composition as Measured in Gale Crater, Mars

The Sample Analysis at Mars (SAM) instrument onboard the Mars Science Laboratory Curiosity rover measures the chemical composition of major atmospheric species (CO2, N2, 40Ar,O2, and CO) through a dedicated atmospheric inlet. We report here measurements of volume mixing ratios in Gale Crater using the SAM quadrupole mass spectrometer, obtained over a period of nearly 5 years (3 Mars years) from landing. The observation period spans the northern summer of MY31 and solar longitude (L(sub S)) of 175° through spring of MY 34, L(sub S) = 12°. This work expands upon prior reports of the mixing ratios measured by SAM QMS in the first 105 sols of the mission. The SAM QMS atmospheric measurements were taken periodically, with a cumulative coverage of four or five experiments per season on Mars. Major observations include the seasonal cycle of CO2, N2, and Ar, which lags approximately 20–40° of L(sub S) behind the pressure cycle driven by CO2 condensation and sublimation from the winter poles. This seasonal cycle indicates that transport occurs on faster timescales than mixing. The mixing ratio of O2 shows significant seasonal and interannual variability, suggesting an unknown atmospheric or surface process at work. The O2 measurements are compared to several parameters, including dust optical depth and trace CH4 measurements by Curiosity. We derive annual mean volume mixing ratios for the atmosphere in Gale Crater: CO2 = 0.951 (±0.003), N2 = 0.0259 (±0.0006), 40Ar = 0.0194 (±0.0004), O2 = 1.61 (±0.09) x 10(exp ‐3), and CO = 5.8 (±0.8) x 10(exp ‐4).

Gale Crater↗
NASA NTRS2020

SEASONAL VARIATION IN THE MEASUREMENT OF GOES-16 ABI CHANNEL-TO-CHANNEL REGISTRATION

An Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) was developed to assess the US Geostationary Operational Environmental Satellite R-series (GOES-R) Advanced Baseline Imager (ABI) and Geostationary Lighting Mapper (GLM) INR performance.Channel-to-channel registration (CCR) is one of the five INR performance metricsproduced by IPATS. A seasonal variationis observed in the CCR assessment in north-south direction when one or both channels are reflective. However, indirect CCR, calculated as the difference of NAV measurements between two channels, does not presentthe similar seasonal variation. The phenomenon of the seasonal variationcoincides with the annual change of the subsolar point location. The amplitude of the seasonal variation is related tothe length and the direction of the shadow. DirectCCR, measured by IPATSdirectly,performs better than indirect CCR when both channels are visible wavelengthsor emissivechannels. For all other channel paircombinations, the assessment of indirect CCR is more accurate.

Bin Tan↗
NASA NTRS2021

Impacts of the Eruption of Mount Pinatubo on Surface Temperatures and Precipitation Forecasts With the NASA GEOS Subseasonal-to-Seasonal System

A contemporary seasonal forecasting system is used to study the impacts of a volcanic sulfate injection into the stratosphere on the seasonal forecasts for surface temperatures, the El Niño Southern Oscillation (ENSO), and precipitation. The focus is a case study of the June 1991 eruption of Mt. Pinatubo, Philippines and the period from July 1991 to February 1992. Version 2 of the Goddard Earth Observing System (GEOS) subseasonal-to-seasonal (S2S) forecasting system is used in this study. GEOS-S2S includes the GOddard Chemistry, Aerosols, Radiation and Transport (GOCART) aerosol module, which allows to prognostically simulate aerosol distributions. GOCART is coupled to the radiation and cloud modules to include the impact of the eruption on forecasted radiation and precipitation. The coupled GEOS-S2S system was initialized in May 1991 with fields based on observations to produce ten-member 9-month forecasts with and without the volcanic sulfur injection. The results of these ensemble experiments demonstrate that including Mt. Pinatubo in seasonal forecasts would improve the forecasts of the 1991–1992 global mean temperature and precipitation but worsen the forecast of ENSO by strengthening of El Niño beyond what showed in observations. Most significant changes in the forecasts of temperatures and precipitation are limited to the tropics. The only land area where the inclusion of Pinatubo significantly lowered the forecasted precipitation is tropical Africa.

Mt. Pinatubo↗
NASA NTRS2022

Seasonal Variation of Thermospheric Composition Observed by NASA GOLD

We examine characteristics of the seasonal variation of thermospheric composition using column number density ratio ∑O/N(2) observed by the NASA Global Observations of Limb and Disk (GOLD) mission from low-mid to mid-high latitudes. We also use ∑O/N(2) derived from the Global Ultraviolet Imager (GUVI) limb measurements onboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite and estimated by the NRLMSISE-00 empirical model to aid our investigation. We found that the ∑O/N(2) seasonal variation is hemispherically asymmetric: in the southern hemisphere, it exhibits the well-known annual and semiannual pattern, with highs near the equinoxes, and primary and secondary lows near the solstices. In the northern hemisphere, it is dominated by an annual variation, with a minor semiannual component with the highs shifting toward the wintertime. We also found that the durations of the December and June solstice seasons in terms of ∑O/N(2) are highly variable with longitude. Our hypothesis is that ion-neutral collisional heating in the equatorial ionization anomaly region, ion drag, and auroral Joule heating play substantial roles in this longitudinal dependency. Finally, the rate of change in ∑O/N(2) from one solstice season to the other is dependent on latitude, with more dramatic changes at higher latitudes.

thermosphere↗
NASA NTRS2023

Aura/MLS Observes and SD-WACCM-X Simulates the Seasonality, Quasi-Biennial Oscillation and El Niño-Southern Oscillation of the Migrating Diurnal Tide Driving Upper Mesospheric CO Primarily Through Vertical Advection

This work uses 17 years of upper mesospheric carbon monoxide (CO) and temperature observations by the Microwave Limb Sounder (MLS) on-board the Aura satellite to present and explain the seasonal and interannual variability of the migrating diurnal tide (DW1) component of upper mesospheric CO. This work then compares these observations to simulations by the Specified Dynamics – Whole Atmosphere Community Climate Model with Ionosphere/Thermosphere eXtension (SD-WACCM-X). Results show that, for all seasons, MLS CO local-time perturbations peaks above 85 km and has a latitude structure resembling the (1,1) mode in temperature. On the other hand, SD-WACCM-X DW1 also peaks above 85 km and has a latitude structure resembling the (1,1) mode but it simulates 2 local maximum of the (1,1) mode between 85 km and 92 km. Despite the differences in altitude structure, a tendency analysis and the adiabatic displacement method revealed that, on seasonal and interannual timescales, observed and modelled CO’s (1,1) component can be reproduced solely using vertical advection. It was also found that both observed and modelled CO’s (1,1) component contains interannual oscillations with periodicities close to that of the Quasi-biennial Oscillation and the El Niño–Southern Oscillation. From these results, this work concludes that on seasonal and interannual timescales, the observed and modelled (1,1) mode affects the global structure of upper mesospheric CO primarily through vertical advection.

Cornelius Csar Jude H Salinas↗