NASA Goddard Earth Sciences Research Articles

Mapping of sea ice concentration using the NASA NIMBUS 5 Electrically Scanning Microwave Radiometer data from 1972–1977

Abstract. The Electrically Scanning Microwave Radiometer (ESMR) instrument onboard the NIMBUS 5 satellite was a one-channel microwave radiometer that measured the 19.35 GHz horizontally polarized brightness temperature (TB) from 11 December 1972 to 16 May 1977. The original tape archive data in swath projection have recently been made available online by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Even though the ESMR was a predecessor of modern multi-frequency radiometers, there are still parts of modern processing methodologies which can be applied to the data to derive the sea ice extent globally. Here, we have reprocessed the entire dataset using a modern processing methodology that includes the implementation of pre-processing filtering, dynamical tie points, and a radiative transfer model (RTM) together with numerical weather prediction (NWP) for atmospheric correction. We present the one-channel sea ice concentration (SIC) algorithm and the model for computing temporally and spatially varying SIC uncertainty estimates. Post-processing steps include resampling to daily grids, land-spillover correction, the application of climatological masks, the setting of processing flags, and the estimation of sea ice extent, monthly means, and trends. This sea ice dataset derived from the NIMBUS 5 ESMR extends the sea ice record with an important reference from the mid-1970s. To make it easier to perform a consistent analysis of sea ice development over time, the same grid and land mask as used for EUMETSAT's OSI-SAF SMMR-based sea-ice climate data record (CDR) were used for our ESMR dataset. SIC uncertainties were included to further ease comparison to other datasets and time periods. We find that our sea ice extent in the Arctic and Antarctic in the 1970s is generally higher than those available from the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC), which were derived from the same ESMR dataset, with mean differences of 240 000 and 590 000 km2, respectively. When comparing monthly sea ice extents, the largest differences reach up to 2 million km2. Such large differences cannot be explained by the different grids and land masks of the datasets alone and must therefore also result from the differences in data filtering and algorithms, such as the dynamical tie points and atmospheric correction. The new ESMR SIC dataset has been released as part of the ESA Climate Change Initiative (ESA CCI) program and is publicly available at https://doi.org/10.5285/34a15b96f1134d9e95b9e486d74e49cf (Tonboe et al., 2023).

Developing Metrics for NASA Earth Science Interdisciplinary Data Products and Services

Metrics are measures that are able to produce quantifiable information. There are many applications of metrics in Earth science data and services; for example, metrics are frequently used to track service performance and progress. In short, developing, collecting and analyzing metrics are essential activities to better support Earth science research, applications, and education. As one of the largest repositories of Earth science data in the world, NASA’s Earth Science Data and Information System (ESDIS) Project supports twelve Distributed Active Archive Centers (DAACs). Standard metrics have been developed by the ESDIS Metrics System (EMS). These metrics are collected and analyzed routinely at each DAAC. As it is expected that the total data volume will continue to grow rapidly, and the timely developed technologies (e.g., cloud computing, AI/ML) will continue to improve data discovery and accessibility, opportunities for developing new data services for the Earth science community will also arise, especially in interdisciplinary research and applications. However, developing such metrics has become a challenge because multiple datasets are often needed. Current metrics are designed for a single predefined dataset or service, a disadvantage for collecting metrics for interdisciplinary data services. In this paper, we assess current metrics using one of the NASA DAACs, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), as an example, to discuss challenges and opportunities, along with recommendations for developing metrics addressing interdisciplinary satellite data products and services. <strong>Highlights</strong> <ul><li>Overview of NASA GES DISC Earth science datasets and services</li><li>Overview of existing metrics collection methods and analysis tools with examples</li><li>Discuss challenges and opportunities in collecting metrics for Earth science interdisciplinary data and services</li></ul>

An 11-year record of XCO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm

Abstract. The Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) on the Japanese Greenhouse gases Observing SATellite (GOSAT) has been returning data since April 2009. The version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 Full Physics (L2FP) retrieval algorithm (Kiel et al., 2019) was used to derive estimates of carbon dioxide (CO2) dry air mole fraction (XCO2) from the TANSO-FTS measurements collected over its first 11 years of operation. The bias correction and quality filtering of the L2FP XCO2 product were evaluated using estimates derived from the Total Carbon Column Observing Network (TCCON) as well as values simulated from a suite of global atmospheric inversion systems (models) which do not assimilate satellite-derived CO2. In addition, the v9 ACOS GOSAT XCO2 results were compared with collocated XCO2 estimates derived from NASA's Orbiting Carbon Observatory-2 (OCO-2), using the version 10 (v10) ACOS L2FP algorithm. These tests indicate that the v9 ACOS GOSAT XCO2 product has improved throughput, scatter, and bias, when compared to the earlier v7.3 ACOS GOSAT product, which extended through mid 2016. Of the 37 million soundings collected by GOSAT through June 2020, approximately 20 % were selected for processing by the v9 L2FP algorithm after screening for clouds and other artifacts. After post-processing, 5.4 % of the soundings (2×106 out of 37×106) were assigned a “good” XCO2 quality flag, as compared to 3.9 % in v7.3 (&lt;1 ×106 out of 24×106). After quality filtering and bias correction, the differences in XCO2 between ACOS GOSAT v9 and both TCCON and models have a scatter (1σ) of approximately 1 ppm for ocean-glint observations and 1 to 1.5 ppm for land observations. Global mean biases against TCCON and models are less than approximately 0.2 ppm. Seasonal mean biases relative to the v10 OCO-2 XCO2 product are of the order of 0.1 ppm for observations over land. However, for ocean-glint observations, seasonal mean biases relative to OCO-2 range from 0.2 to 0.6 ppm, with substantial variation in time and latitude. The ACOS GOSAT v9 XCO2 data are available on the NASA Goddard Earth Science Data and Information Services Center (GES-DISC) in both the per-orbit full format (https://doi.org/10.5067/OSGTIL9OV0PN, OCO-2 Science Team et al., 2019b) and in the per-day lite format (https://doi.org/10.5067/VWSABTO7ZII4, OCO-2 Science Team et al., 2019a). In addition, a new set of monthly super-lite files, containing only the most essential variables for each satellite observation, has been generated to provide entry level users with a light-weight satellite product for initial exploration (CaltechDATA, https://doi.org/10.22002/D1.2178, Eldering, 2021). The v9 ACOS Data User's Guide (DUG) describes best-use practices for the GOSAT data (O'Dell et al., 2020). The GOSAT v9 data set should be especially useful for studies of carbon cycle phenomena that span a full decade or more and may serve as a useful complement to the shorter OCO-2 v10 data set, which begins in September 2014.

PBL Height From AIRS, GPS RO, and MERRA‐2 Products in NASA GES DISC and Their 10‐Year Seasonal Mean Intercomparison

AbstractWithin the planetary boundary layer (PBL), surface forcing response, drag, turbulence, and vertical mixing are important processes and play a more critical role here than in the overlying “free atmosphere.” The PBL height (PBLH) is an important parameter in climate models, weather forecasts, and air quality prediction. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides data processing, archiving, and distribution services for numerous Earth science products. PBLH is a parameter in three products served by GES DISC, which are from the atmospheric infrared sounder (AIRS), the global positioning system (GPS) radio occultation (RO) experiment, and the NASA reanalysis product Modern‐Era Retrospective analysis for Research and Applications‐2 (MERRA‐2). These products have different spatial and temporal resolutions and coverages, and their PBLH definitions are also different. To better serve the PBL research community, we have summarized the specifications of these products. A 10‐year seasonal mean intercomparison is also conducted to provide further guidance to users. The intercomparison results show that MERRA‐2 has a much shallower PBL than AIRS and GPS RO. An experimental study indicates that the different PBLH definition in MERRA‐2 caused smaller values of PBLH. The improvement of the water vapor retrieval in AIRS version 7 over version 6 results in the version 7 PBLH agreeing better with GPS RO and MERRA‐2 than version 6, especially near the equator and low latitudes.

Spatio-Temporal Dynamics of Plasmodium falciparum and Plasmodium vivax in French Guiana: 2005-2019.

Aims: This study examines the dynamics of malaria as influenced by meteorological factors in French Guiana from 2005 to 2019. It explores spatial hotspots of malaria transmission and aims to determine the factors associated with variation of hotspots with time. Methods: Data for individual malaria cases came from the surveillance system of the Delocalized Centers for Prevention and Care (CDPS) (n = 17) from 2005–2019. Meteorological data was acquired from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) database. The Box–Jenkins autoregressive integrated moving average (ARIMA) model tested stationarity of the time series, and the impact of meteorological indices (issued from principal component analysis—PCA) on malaria incidence was determined with a general additive model. Hotspot characterization was performed using spatial scan statistics. Results: The current sample includes 7050 eligible Plasmodium vivax (n = 4111) and Plasmodium falciparum (n = 2939) cases from health centers across French Guiana. The first and second PCA-derived meteorological components (maximum/minimum temperature/minimum humidity and maximum humidity, respectively) were significantly negatively correlated with total malaria incidence with a lag of one week and 10 days, respectively. Overall malaria incidence decreased across the time series until 2017 when incidence began to trend upwards. Hotspot characterization revealed a few health centers that exhibited spatial stability across the entire time series: Saint Georges de l’Oyapock and Antecume Pata for P. falciparum, and Saint Georges de l’Oyapock, Antecume Pata, Régina and Camopi for P. vivax. Conclusions: This study highlighted changing malaria incidence in French Guiana and the influences of meteorological factors on transmission. Many health centers showed spatial stability in transmission, albeit not temporal. Knowledge of the areas of high transmission as well as how and why transmission has changed over time can inform strategies to reduce the transmission of malaria in French Guiana. Hotspots should be further investigated to understand other influences on local transmission, which will help to facilitate elimination.

Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments

Abstract. We present a new and improved version (V4.0) of the NASA standard nitrogen dioxide (NO2) product from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This version incorporates the most salient improvements for OMI NO2 products suggested by expert users and enhances the NO2 data quality in several ways through improvements to the air mass factors (AMFs) used in the retrieval algorithm. The algorithm is based on the geometry-dependent surface Lambertian equivalent reflectivity (GLER) operational product that is available on an OMI pixel basis. GLER is calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) instruments over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance. The GLER combined with consistently retrieved oxygen dimer (O2–O2) absorption-based effective cloud fraction (ECF) and optical centroid pressure (OCP) provide improved information to the new NO2 AMF calculations. The new AMFs increase the retrieved tropospheric NO2 by up to 50 % in highly polluted areas; these differences arise from both cloud and surface BRDF effects as well as biases between the new MODIS-based and previously used OMI-based climatological surface reflectance data sets. We quantitatively evaluate the new NO2 product using independent observations from ground-based and airborne instruments. The new V4.0 data and relevant explanatory documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/, last access: 8 November 2020), and we encourage their use over previous versions of OMI NO2 products.

Severe Drought in the Spring of 2020 in Poland—More of the Same?

Two consecutive dry years, 2018 and 2019, a warm winter in 2019/20, and a very dry spring in 2020 led to the development of severe drought in Poland. In this paper, changes in the Standardized Precipitation-Evapotranspiration Index (SPEI) for the interval from 1971 to the end of May 2020 are examined. The values of SPEI (based on 12, 24 and 30 month windows, i.e., SPEI 12, SPEI 24 and SPEI 30) were calculated with the help of the Penman–Monteith equation. Changes in soil moisture contents were also examined from January 2000 to May 2020, based on data from the NASA Goddard Earth Sciences Data and Information Services Center, presenting increasing water shortages in a central belt of Poland. The study showed that the 2020 spring drought was among the most severe events in the analyzed period and presented decreasing trends of SPEI at most stations located in central Poland. This study also determined changes in soil moisture contents from January 2000 to May 2020 that indicate a decreasing tendency. Cumulative water shortages from year to year led to the development of severe drought in the spring of 2020, as reflected in very low SPEI values and low soil moisture.

OCO-3 early mission operations and initial (vEarly) XCO2 and SIF retrievals

NASA's Orbiting Carbon Observatory-3 (OCO-3) was installed on the International Space Station (ISS) on 10 May 2019. OCO-3 combines the flight spare spectrometer from the Orbiting Carbon Observatory-2 (OCO-2) mission, which has been in operation since 2014, with a new Pointing Mirror Assembly (PMA) that facilitates observations of non-nadir targets from the nadir-oriented ISS platform. The PMA is a new feature of OCO-3, which is being used to collect data in all science modes, including nadir (ND), sun-glint (GL), target (TG), and the new snapshot area mapping (SAM) mode.This work provides an initial assessment of the OCO-3 instrument and algorithm performance, highlighting results from the first 8 months of operations spanning August 2019 through March 2020. During the In-Orbit Checkout (IOC) phase, critical systems such as power and cooling were verified, after which the OCO-3 spectrometer and PMA were subjected to a series of rigorous tests. First light of the OCO-3 spectrometer was on 26 June 2019, with full science operations beginning on 6 August 2019. The OCO-3 spectrometer on-orbit performance is consistent with that seen during preflight testing. Signal to noise ratios are in the expected range needed for high quality retrievals of the column-averaged carbon dioxide (CO2) dry-air mole fraction (XCO2) and solar-induced chlorophyll fluorescence (SIF), which will be used to help quantify and constrain the global carbon cycle.The first public release of OCO-3 Level 2 (L2) data products, called “vEarly”, is being distributed by NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC). The intent of the vEarly product is to evaluate early mission performance, facilitate comparisons with OCO-2 products, and identify key areas to improve for the next data release. The vEarly XCO2 exhibits a root-mean-squared-error (RMSE) of ≃ 1, 1, 2 ppm versus a truth proxy for nadir-land, TG&SAM, and glint-water observations, respectively. The vEarly SIF shows a correlation with OCO-2 measurements of >0.9 for highly coincident soundings. Overall, the Level 2 SIF and XCO2 products look very promising, with performance comparable to OCO-2. A follow-on version of the OCO-3 L2 product containing a number of refinements, e.g., instrument calibration, pointing accuracy, and retrieval algorithm tuning, is anticipated by early in 2021.

NASA Global Satellite and Model Data Products and Services for Tropical Meteorology and Climatology

Satellite remote sensing and model data play an important role in research and applications of tropical meteorology and climatology over vast, data-sparse oceans and remote continents. Since the first weather satellite was launched by NASA in 1960, a large collection of NASA’s Earth science data is freely available to the research and application communities around the world, significantly improving our overall understanding of the Earth system and environment. Established in the mid-1980s, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), located in Maryland, USA, is a data archive center for multidisciplinary, satellite and model assimilation data products. As one of the 12 NASA data centers in Earth sciences, GES DISC hosts several important NASA satellite missions for tropical meteorology and climatology such as the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM) Mission and the Modern-Era Retrospective analysis for Research and Applications (MERRA). Over the years, GES DISC has developed data services to facilitate data discovery, access, distribution, analysis and visualization, including Giovanni, an online analysis and visualization tool without the need to download data and software. Despite many efforts for improving data access, a significant number of challenges remain, such as finding datasets and services for a specific research topic or project, especially for inexperienced users or users outside the remote sensing community. In this article, we list and describe major NASA satellite remote sensing and model datasets and services for tropical meteorology and climatology along with examples of using the data and services, so this may help users better utilize the information in their research and applications.

The version 3 OMI NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; standard product

Abstract. We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry–transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ∼ 10–40 %) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2).

The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) is the latest atmospheric reanalysis of the modern satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observation types not available to its predecessor, MERRA, and includes updates to the Goddard Earth Observing System (GEOS) model and analysis scheme so as to provide a viable ongoing climate analysis beyond MERRA's terminus. While addressing known limitations of MERRA, MERRA-2 is also intended to be a development milestone for a future integrated Earth system analysis (IESA) currently under development at GMAO. This paper provides an overview of the MERRA-2 system and various performance metrics. Among the advances in MERRA-2 relevant to IESA are the assimilation of aerosol observations, several improvements to the representation of the stratosphere including ozone, and improved representations of cryospheric processes. Other improvements in the quality of MERRA-2 compared with MERRA include the reduction of some spurious trends and jumps related to changes in the observing system, and reduced biases and imbalances in aspects of the water cycle. Remaining deficiencies are also identified. Production of MERRA-2 began in June 2014 in four processing streams, and converged to a single near-real time stream in mid 2015. MERRA-2 products are accessible online through the NASA Goddard Earth Sciences Data Information Services Center (GES DISC).

Global Precipitation Measurement (GPM) Mission Products and Services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC).

This article describes NASA/JAXA Global Precipitation Measurement (GPM) mission products and services at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). Built on the success of the Tropical Rainfall Measuring Mission (TRMM), the next generation GPM mission consists of new precipitation measurement instruments and a constellation of international research and operational satellites to provide improved measurements of precipitation globally. To facilitate data access, research, applications, and scientific discovery, the GES DISC has developed a variety of data services for GPM. This article is intended to guide users in choosing GPM datasets and services at the GES DISC.

A land data assimilation system for sub-Saharan Africa food and water security applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Comparison of Atmospheric Methane Retrievals From AIRS and IASI

Atmospheric methane (CH4) is a standard product of the atmospheric infrared sounder (AIRS) aboard NASA's Aqua satellite, generated at the NASA Goddard Earth Sciences Data and Information Services Center (NASA/GES/DISC), and a product of the infrared atmospheric sounding interferometer (IASI) aboard METOP-A,-B, generated at National Oceanic and Atmospheric Administration's Comprehensive Large Array-data Stewardship System. In order to understand the capability of these two sensors in observing the spatial and temporal distribution of CH4 , this paper compares the CH4 products from AIRS and IASI with aircraft measurements, as well as the corresponding time series in tropics and high northern latitude regions. It is found that the mean degree of freedom from AIRS is smaller than IASI by –0.049 ± 0.152, and in their peak sensitive altitude between 350 and 650 hPa their difference (AIRS – IASI) is about 2.8 ± 17.2 ppb. Both AIRS and IASI can capture the latitudinal gradient, but there is a large scattering in the high northern latitude regions. They agree well in observing the summer enhancement of CH4 during the Monsoon season over South Asia, and the seasonal cycles over Siberia (except for a relatively larger difference in the cold season). These results highlight that AIRS and IASI can provide valuable information to capture the spatiotemporal variation of CH4 in the mid-upper troposphere in most periods and regions, but it is needed to further improve the data quality to make a consistent product using both sensors.

Advances in &lt;inline-formula&gt; &lt;tex-math notation="TeX"&gt; $\hbox{CO}_{2}$&lt;/tex-math&gt;&lt;/inline-formula&gt; Observations From AIRS and ACOS

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 (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ). Most recently, the Atmospheric CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> Observations from Space (ACOS) project and GES DISC released CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> 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 CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> from AIRS, as well as the most recent status of the total column-average distribution of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> from ACOS. We also demonstrate that significant discrepancies still exist in the global distribution of observed and modeled column amounts of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> using the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> retrievals from the ACOS project.

Deforestation‐induced reduction in rainfall

Copyright © 2013 John Wiley & Sons, Ltd. Borneo is the third largest island in the world and famous for its majestic rainforests (Figure 1a). Southeast Asian tropical forests have the highest relative deforestation rate in the world (Canadell et al., 2007). More than 80% of the total land area of Borneo was covered with pristine forest in the 1950s; however, the high deforestation rate (1.7%year ), which is almost double that of the already intense deforestation rate of the whole Southeast Asian region, has resulted in the current estimation of forest cover being ~50% (Langner et al., 2007) (Figure 1b). Since 1965, production of tropical hardwood timber in Borneo sharply increased and reached a plateau and maximum in the early 1980s (Brookfield and Byron, 1990). Although the recent and rapid decline in timber production has been evident throughout Borneo owing to over-logging, over the past decades, more timber was exported from Borneo than from tropical Africa and Latin America combined (Curran et al., 2004). The land cover area categorized as ‘degraded forest and regrowth’, ‘cultivation forest mosaic’ and ‘dry/wet bare soil; grasslands; agriculture’ reached up to 33 million ha, ~45% of the total area of Borneo (Langner et al., 2007). Tropical forests are a major source of global hydrologic fluxes, and thus, this forest cover change has potential to significantly alter the global and regional climate and hydrologic cycling (Nobre et al., 1991;Kanae et al., 2001; Avissar andWerth, 2005). Because tropical rainforests exist where ecosystem water resources are greatest, the hydrologic changes could significantly alter ecological patterns and processes (Malhi et al., 2009; Phillips et al., 2009; Kumagai and Porporato, 2012), in turn affecting feedback to the atmosphere (Meir et al., 2006; Bonan, 2008). It is a matter of course that the drastic deforestation and forest degradation in Borneo should be anticipated to impact the regional hydro-climate; in fact, the long-term daily grid precipitation datasets (APHRODITE’s Water Resources, available via http://www.chikyu.ac.jp/precip/, Yatagai et al., 2012) over Borneo showed a significant decline in precipitation over the period 1951–2007 (Figure 1c). An abrupt decline in precipitation in the late 1980s can be seen (Figure 1c), which was consistent with a time when deforestation, i.e. logging for timber production, might have become intensive (Brookfield and Byron, 1990; Curran et al., 2004). Furthermore, it should be noted that such a decreasing trend in precipitationmight cause frequent extreme droughts and subsequent fires, resulting in more severe deforestation and forest degradation (van Nieuwstadt and Sheil, 2005; Wooster et al., 2012). A spatial distribution of atmospheric moisture convergence averaged over 1998–2010 in the eastern Pacific Ocean (built using a reanalyzed and gridded four-dimensional meteorology dataset, Japanese 25-year ReAnalysis and the JapanMeteorologicalAgencyClimateDataAssimilation System available via http://jra.kishou.go.jp/JRA-25/index_en.html) suggests less moisture convergence and divergence over Borneo compared with other regions (Figure 2a). On the other hand, the Tropical Rainfall Measuring Mission satellite measurements from 1998 to 2010 (NASA Goddard Earth Sciences Data and Information Services Center, available via http://disc.sci.gsfc.nasa.gov/ about-us) showed a larger amount of precipitation above islands of the maritime continent in the western Pacific Ocean compared with sea areas,

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.–Japan satellite mission to provide the first detailed and comprehensive dataset of the four-dimensional distribution of rainfall and latent heating over vastly undersampled tropical and subtropical oceans and continents (40°S–40°N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological, and other research and application activities around the world. This short article describes how the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and nearreal- time precipitation datasets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor's resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Opensource Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data-related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission, which is scheduled for launch in 2014.

MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications

Abstract The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).

Giovanni: A Web Service Workflow-Based Data Visualization and Analysis System

NASA's Goddard Earth Sciences Data and Information Services Center has developed the Goddard Interactive Online Visualization ANd aNalysis Infrastructure or ldquoGiovanni,rdquo an asynchronous Web-service-based workflow management system for Earth science data. Giovanni has been providing an intuitive and responsive interface for visualizing, analyzing, and intercomparing multisensor data using only a Web browser to scientists and other users. Giovanni supports many types of single- and multiparameter visualizations and statistical analyses. The interface also provides users with capabilities for downloading images and data in multiple formats. Giovanni supports open and standard data protocols and formats. Finally, Giovanni provides users with a data lineage that describes, in detail, the algorithms used in processing the data including caveats and other scientifically pertinent information.

Multi‐sensor data fusion and comparison of total column ozone

With many remote‐sensing instruments onboard satellites exploring the Earth's atmosphere, most data are processed to gridded daily maps. However, differences in the original spatial, temporal, and spectral resolution—as well as format, structure, and temporal and spatial coverage—make the data merging, or fusion, difficult. NASA Goddard Earth Sciences Data and Information Services Center (GES‐DISC) has archived several data products for various sensors in different formats, structures, and multi‐temporal and spatial scales for ocean, land, and atmosphere. In this investigation using Earth science data sets from multiple sources, an attempt was made to develop an optimal technique to merge the atmospheric products and provide interactive, online analysis tools for the user community. The merged/fused measurements provide a more comprehensive view of the atmosphere and improve coverage and accuracy, compared with a single instrument dataset. This paper describes ways of merging/fusing several NASA Earth Observing Systems (EOS) remote‐sensing datasets available at GES‐DISC. The applicability of various methods was investigated for merging total column ozone to implement these methods into Giovanni, the online interactive analysis tool developed by GES‐DISC. Ozone data fusion of MODerate resolution Imaging Spectrometer (MODIS) Terra and Aqua Level‐3 daily data sets was conducted, and the results were found to provide better coverage. Weighted averaging of Terra and Aqua data sets, with the consequent interpolation through the remaining gaps using Optimal Interpolation (OI), also was conducted and found to produce better results. Ozone Monitoring Instrument (OMI) total column ozone is reliable and provides better results than Atmospheric Infrared Sounder (AIRS) and MODIS. However, the agreement among these instruments is reasonable. The correlation is high (0.88) between OMI and AIRS total column ozone, while the correlation between OMI and MODIS Terra/Aqua fused total column ozone is 0.79.