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NASA NTRS2018

Representativeness of CO and O3 Along ATom Transects Derived from GEOS-5 and GMI-CTM Simulations

One major goal for the NASA Atmospheric Tomography Mission (ATom) is producing an observation-based chemical climatology to represent the atmospheric heterogeneity. In this study, we use CO and O3 observations and global atmospheric model simulations to examine the spatial representativeness of the ATom-1 and -2 transects within a 4D framework provided by the NASA GEOS-5 and GMI-CTM models. Based on the probability density functions, we find that the variability of CO and O3 along the flight tracks is well hindcast by the model when sampled per ATom flights. The CO variations along the ATom-transect are likely representative of the typical CO variations over the whole Pacific basin during both the ATom-1 and -2 periods, the northern Atlantic during the ATom-1 period, and the tropical Atlantic in the ATom-2 period. Over southern Atlantic, CO along the ATom-1 transects is likely less well mixed than that of the broader region, but is still representative of the median CO concentration. CO along the ATom-2 transect is likely higher than the median CO concentration over this region. For O3, the agreements between PDFs of O3 sampled along the ATom transects and over the broader regions are fair to good over all six regions (Scores > 0.65) with notable discrepancies over some regions. For example, in ATom-1 over the northern Pacific and Atlantic, the transect samples air masses with higher O3 levels. During ATom-2, the transect over-represents the occurrence of O3 plumes over tropical Pacific. Over the southern Pacific and Atlantic for both ATom-1 and -2, the transects have a less uniform distribution compared to the surrounding basins, but still represent the median O3 abundance. Overall, we conclude in most cases that ATom measurements represent the statistical variations of these two species over the ocean basins at the time of measurement. Higher-order statistics, including covariance of species, has not been tested in this study.

ozone↗

NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

NASA NTRS2015

Technical Report Series on Global Modeling and Data Assimilation: Soil Moisture Active Passive (SMAP) Project Assessment Report for the Beta-Release L4_SM Data Product - Volume 40

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public beta release scheduled for 30 October 2015. The primary objective of the beta release is to allow users to familiarize themselves with the data product before the validated product becomes available. The beta release also allows users to conduct their own assessment of the data and to provide feedback to the L4_SM science data product team. The assessment of the L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to upscaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 1 validation and supports the beta release of the data. The validation against sparse network measurements and the evaluation of the assimilation diagnostics address Stage 2 validation criteria by expanding the assessment to regional and global scales.

ubRMSE↗

NASA NTRS2000

Performance of the GEOS-3/Terra Data Assimilation System in the Northern Stratospheric Winter 1999/2000

As part of NASA's support for the Terra satellite, which became operational in January 2000, the Data Assimilation Office introduced a new version of the GEOS data assimilation system (DAS) in November 1999. This system, GEOS-3/Terra, differs from its predecessor in several ways, notably through an increase in horizontal resolution (from 2-by-2.5 degrees to 1-by-1 degree), a slightly lower upper boundary (0.1 instead of 0.01hPa) with fewer levels (48 as opposed to 70), and substantial changes to the tropospheric physics package. This paper will address the performance of the GEOS-3/Terra DAS in the stratosphere. it focusses on the analyses (produced four times daily) and the five-day forecasts (produced twice daily). These were important for the meteorological support of the SAGE-3 Ozone Loss and Validation Experiment, based in Kiruna, Northern Sweden, in the winter of 1999/2000. It is shown that the analyses of basic meteorological fields (temperature, geopotential height, and horizontal wind) are in good agreement with those from other centers. The analyses captured the cold polar vortex which persisted through most of the winter. It is shown that forecasts (up to five days) tend to have a warm bias, which is important for the prediction of polar stratospheric clouds, which are triggered by temperatures of 195K (or lower). The importance of accurate upper tropospheric forecasts in predicting the stratospheric flow is highlighted in the context of the evolution of the shape of the stratospheric polar vortex. A prominent blocking high in the Atlantic region in January was an important factor determining the shape of the distorted lower stratospheric vortex; the predictive skill of these features was strongly coupled in the GEOS-3/Terra system.

Pawson, S.↗