Andrey Savtchenko

A-Train data depot - bringing Atmospheric measurements together

This paper describes the satellite data processing and services that constitute current functionalities of the A-Train Data Depot. We first provide a brief introduction to the original geometrical intricacies of the platforms and instruments of the A-Train constellation and then proceed with a description of our A-Train collocation-processing algorithm that provides subsets that facilitate synergistic use of the various instruments. Finally, we present some sample image products from our web-based Giovanni tool which allows users to display, compare, and download coregistered A-Train-related data.

Estimating Sampling Biases and Measurement Uncertainties of AIRS-AMSU-A Temperature and Water Vapor Observations Using MERRA Reanalysis

We use MERRA (Modern Era Retrospective-Analysis for Research Applications) temperature and water vapor data to estimate the sampling biases of climatologies derived from the AIRS/AMSU-A (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A) suite of instruments. We separate the total sampling bias into temporal and instrumental components. The temporal component is caused by the AIRS/AMSU-A orbit and swath that are not able to sample all of time and space. The instrumental component is caused by scenes that prevent successful retrievals. The temporal sampling biases are generally smaller than the instrumental sampling biases except in regions with large diurnal variations, such as the boundary layer, where the temporal sampling biases of temperature can be ± 2 K and water vapor can be 10% wet. The instrumental sampling biases are the main contributor to the total sampling biases and are mainly caused by clouds. They are up to 2 K cold and > 30% dry over midlatitude storm tracks and tropical deep convective cloudy regions and up to 20% wet over stratus regions. However, other factors such as surface emissivity and temperature can also influence the instrumental sampling bias over deserts where the biases can be up to 1 K cold and 10% wet. Some instrumental sampling biases can vary seasonally and/or diurnally. We also estimate the combined measurement uncertainties of temperature and water vapor from AIRS/AMSU-A and MERRA by comparing similarly sampled climatologies from both data sets. The measurement differences are often larger than the sampling biases and have longitudinal variations.

Assessment of Precipitation Anomalies in California Using TRMM and MERRA Data

Using modern satellite (Tropical Rainfall Measuring Mission, TRMM, 1998–2014) and reanalysis (Modern-Era Retrospective Analysis for Research and Applications, MERRA, 1979–2015) data, we reassess certain aspects of the precipitation climate in California from the past decades. California has a well-pronounced rain season that peaks in December–February. However, the 95% confidence interval around the climatological precipitation during these months imply that deviations on the order of 60% of the expected amounts are very likely during the most important period of the rain season. While these positive and negative anomalies alternate almost every year and tend to cancel each other, severe multiyear declines of precipitation in California appear on decadal scales. The 1986–1994 decline of precipitation was similar to the current one that started in 2011 and is apparent in the reanalysis data. In terms of accumulated deficits of precipitation, that episode was no less severe than the current one. While El Nino (the warm phase of the El Nino–Southern Oscillation, ENSO) is frequently cited as the natural forcing expected to bring a relief from drought, our assessment is that ENSO has been driving at best only 6% of precipitation variability in California in the past three decades. Using fractional risk analysis of precipitation during typical versus drying periods, we show that the likelihood of losing the most intensive precipitation events drastically increases during the multiyear drying events. Storms delivering up to 50% of the precipitation in California are driven by atmospheric rivers making landfall. However, these phenomena can be suppressed and even blocked by persistent ridges of atmospheric pressure in the northeast Pacific. The reanalysis and satellite data are proven to be reliable to the extent where they yield information on developing conditions and observed precipitation anomalies.

MODIS data from Terra and Aqua satellites

The Moderate-resolution Imaging Spectroradiometer (MODIS) mission is entering its fourth year of successful operation and has yielded staggering amounts of data types and volumes. After the first MODIS launch in November 1999 on board the Tera satellite, a second instrument was bought to orbit on board of the Aqua satellite in May 2002. Both instruments can provide global coverage in 250-1000 m resolutions in just one day. The distribution of all MODIS data by any single NASA Distributed Active Archive Center (DAAC) is not feasible. Thus, the Goddard Earth Sciences (GES) DAAC produces Level 1A and 1B, and distributes the latter as well as the higher level of Ocean and Atmosphere products. Our goal is to give a generic picture of MODIS products and services available from GES DAAC, intended for users introducing themselves to the MODIS mission.

Effect of large eddies on atmospheric surface layer turbulence and the underlying wave field

To improve existing models for air-sea interaction, a better understanding of the energy transfer across the boundary layer and in particular of the coupling of large atmospheric eddies with the air-sea interface is needed. Recent investigations have already shown a possible coupling of large structures in atmospheric turbulence and surface ripples. This was done using synthetic aperture radar (SAR) imagery of ocean surface and almost simultaneous advanced very high resolution radiometer (AVHRR) imagery of cloud streets at a cold-air outbreak. The intent of our study is to further validate this hypothesis in a general case of coastal circulation. For this purpose we analyze a suite of collocated simultaneous records of airflow, radar return, and surface elevations from a coastal platform. We investigate the influence of large eddies (20–60 min) on the turbulent properties of the airflow in the first 2 m above the ocean surface. The analysis shows very prominent peaks in the magnitude of 12- to 16-min fluctuations which are further modulated in 20- to 40-min intervals. These scales and modulations are characteristic for all variables of interest here. The detected scales and their modulation suggest significant interaction of surface layer within the first 1–2 m with large eddies of scales of O(1) and O(10) km. The intermittent structure of turbulence responds by alternating contributions from bursts and sweeps; the frequency of occurrence of bursts and sweeps also reveals the influence of large structures. The instantaneous cross correlation between the shorter scales of momentum flux and radar return, corresponding to the individual burst events, can be 4 times as strong as the overall cross correlation.

Advances in

NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archives and distributes pioneering collections of data on atmospheric greenhouse gases. In September of 2012, the Atmospheric Infrared Sounder (AIRS) marked a decade of tropospheric observations of carbon dioxide (CO2). Most recently, the Atmospheric CO2 Observations from Space (ACOS) project and GES DISC released CO2 retrievals derived from radiances observed by the Japanese Greenhouse gases Observing SATellite (GOSAT) satellite, launched in 2009. In this letter, we present the most recent estimates of decadal mid-tropospheric trends of CO2 from AIRS, as well as the most recent status of the total column-average distribution of CO2 from ACOS. We also demonstrate that significant discrepancies still exist in the global distribution of observed and modeled column amounts of CO2 using the CO2 retrievals from the ACOS project.

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Abstract The unique position of the NASA Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), as an intermediary between users and Terra and Aqua/MODIS data, let us to explore and develop tools that could help users access and manipulate data. The search and order tools include DAAC-unique extensions such as: the Web-based hierarchical ordering mechanism, the multi-product ordering system, and moderate-resolution imaging spectroradiometer (MODIS) Level 1B channel subsetting. Visualization and data manipulation tools, exemplified by HDFLook_MODIS, resulted from a joint collaboration between GES DAAC, University of Science and Technology, Lillie, and MODIS Science team; furthermore, simple interactive data language (IDL) tools were developed at GES DAAC as work aids. The key features of some of the improved tools available from the GES DAAC are described.

Observations From AIRS and ACOS

This study compares horizontal gradients of sea surface temperature (SST) observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard of Terra satellite with those in the Reynolds analysis. Large differences exists in the horizontal gradients between the two SST products, suggesting that existing surface heat balance analyses based on the Reynolds SST analysis is inaccurate. Impact of the inaccuracies on the surface heat balance of the equatorial Pacific region during 2001-02 is estimated. Sensitivity of the SST horizontal gradients with respect to the grid resolution of the data is also studied and the importance of horizontal diffusion in surface heat balance of the coarse-resolution grid is suggested.

GES DAAC tools for accessing Terra and Aqua MODIS data

The immense potential for new science findings as a result of inter-instrument data analysis has led to the development of a new data portal at GSFC: the A-train Data Depot. The power and utility of this new service to the general public is amplified immensely when the archived data are used in conjunction with online data analysis services like Giovanni. This presentation details some of the challenges of data usage from multiple distinct missions and how the tool sets we have developed can help to overcome these challenges, considerably cut down on analysis overhead and promote science exploration in an otherwise very challenging arena.

Horizontal sea surface temperature gradients: MODIS satellite observations versus Reynolds analysis

The immense potential for new science findings as a result of inter-instrument data analysis has led to the development of a new data portal at GSFC: the A-Train Data Depot (ATDD). The power and utility of this new service to the research community is amplified immensely when the archived data are used in conjunction with online data analysis services like Giovanni. This presentation details some of the challenges of data usage from multiple distinct missions and how the tool sets we have developed can help to overcome these challenges, considerably cut down on analysis overhead and promote science exploration in an otherwise very challenging arena.