Alfred M. Powell

Use of Satellite and In-Situ Data to Improve Sustainability

Lipinskiy, O.: A system for detection and monitoring of natural disasters in Ukraine. Ukrainian National Committee on Hydrometeorology , Kyiv, UKRAINE Kleshenko, A.: Space observations for environmental monitoring in Russia. Institute for Agricultural Meteorology, Roshydromet, Obninsk, RUSSIA Robinson, C.: Support for International Cooperative Research in Climate Change and the Environment. U.S. Civilian Research & Development Foundation (CRDF). Arlington, VA, USA

Satellite-based applications on climate change

From the Contents: Introduction to Satellite Remote Sensing of Climate.- Overview of Satellite-based Measurements and Applications.- Calibrating A System of Satellites.- MODIS Ten Year Performance to Support Climate Change Study.- Introduction to NOAA Climate Data Record Program.- Comparison of Trends and Solar Forcing in MSU, ERA-40 and NCEP/NCAR Analysis of Stratospheric and Tropospheric Temperature in the period of 1979-2002.- Development of the Global Mutispectral Imager Thermal Emissive FCDRs.- Atmospheric and climate applications.- Global Precipitation Monitoring.- Developing a Historical Precipitation Record.- Atmospheric Temperature Climate Data Records from Satellite Microwave Sounders.

S4: An O2R/R2O Infrastructure for Optimizing Satellite Data Utilization in NOAA Numerical Modeling Systems: A Step Toward Bridging the Gap between Research and Operations

AbstractIn 2011, the National Oceanic and Atmospheric Administration (NOAA) began a cooperative initiative with the academic community to help address a vexing issue that has long been known as a disconnection between the operational and research realms for weather forecasting and data assimilation. The issue is the gap, more exotically referred to as the “valley of death,” between efforts within the broader research community and NOAA’s activities, which are heavily driven by operational constraints. With the stated goals of leveraging research community efforts to benefit NOAA’s mission and offering a path to operations for the latest research activities that support the NOAA mission, satellite data assimilation in particular, this initiative aims to enhance the linkage between NOAA’s operational systems and the research efforts. A critical component is the establishment of an efficient operations-to-research (O2R) environment on the Supercomputer for Satellite Simulations and Data Assimilation Studies ...

Use of SSU/MSU Satellite Observations to Validate Upper Atmospheric Temperature Trends in CMIP5 Simulations

The tropospheric and stratospheric temperature trends and uncertainties in the fifth Coupled Model Intercomparison Project (CMIP5) model simulations in the period of 1979–2005 have been compared with satellite observations. The satellite data include those from the Stratospheric Sounding Units (SSU), Microwave Sounding Units (MSU), and the Advanced Microwave Sounding Unit-A (AMSU). The results show that the CMIP5 model simulations reproduced the common stratospheric cooling (−0.46–−0.95 K/decade) and tropospheric warming (0.05–0.19 K/decade) features although a significant discrepancy was found among the individual models being selected. The changes of global mean temperature in CMIP5 simulations are highly consistent with the SSU measurements in the stratosphere, and the temporal correlation coefficients between observation and model simulations vary from 0.6–0.99 at the 99% confidence level. At the same time, the spread of temperature mean in CMIP5 simulations increased from stratosphere to troposphere. Multiple linear regression analysis indicates that the temperature variability in the stratosphere is dominated by radioactive gases, volcanic events and solar forcing. Generally, the high-top models show better agreement with observations than the low-top model, especially in the lower stratosphere. The CMIP5 simulations underestimated the stratospheric cooling in the tropics and overestimated the cooling over the Antarctic compared to the satellite observations. The largest spread of temperature trends in CMIP5 simulations is seen in both the Arctic and Antarctic areas, especially in the stratospheric Antarctic.

Global land vegetation and marine fishery responses to atmospheric and oceanic decadal variability

The decadal variability of sea surface temperature (SST) and sea level pressure (SLP) anomalies, as well as the response of global land vegetation and marine fisheries, are investigated for three periods: 1982–1988, 1989–1998, and 1999–2008, separated by the 1988–89 and 1998–99 regime shifts. The goal is to develop a global-scale ecosystem concept to support an improved understanding of the corresponding changes in atmospheric, oceanic, and biological responses. The analysis is based on global SST, SLP, precipitable water content (PWC), land vegetation condition index (VCI), and the United Nations Food and Agriculture Organization’s (FAO) fish capture data. The results show that SST and SLP displayed significant decadal variability. The decadal variability of sea surface temperature anomalies (SSTA) associated with sea level pressure anomalies (SLPA) has an influence on the land vegetation moisture condition (VCI). Positive SSTA tends to be associated with negative SLPA, and vice versa, in the corresponding ocean areas and most land areas. Consequently, clearly opposing distributions of SSTA and SLPA are observed in the periods 1982–1988 and 1999–2008. With positive SSTA and negative SLPA, VCI tends to increase in value representing more favourable vegetation conditions. Negative SSTA and positive SLPA is generally unfavourable for global vegetation development. The decadal variability of SSTA is closely related to the number of fish species (NFS) doing better or worse based on normalized fish landing data. However, the fishery responses show different yet consistent trends in the three ocean basins. When SSTA is negative, it appears more beneficial for the number of fish species with improved landings in the Atlantic Ocean. However, positive SSTA leads to more fish species with improved landings in the Indian and Pacific Oceans.

Evaluation of the Temperature Trend and Climate Forcing in the Pre- and Post Periods of Satellite Data Assimilation

Based on multiple linear regression analysis, three temperature datasets from two reanalyses and one set of satellite observations have been used to evaluate the different responses in the winter [December–February (DJF)] period in the pre- and post periods of satellite data assimilation as they relate to a selected set of climate forcings: solar, the stratospheric quasi-biennial oscillation (QBO), El Nino Southern Oscillation (ENSO), and stratospheric aerosol optical depth (AOD). The two periods are defined as 1958–1978 when no satellite data was available to be assimilated and the 1979–2002 period when satellite data was assimilated in the operational forecast models. The multiple regression analysis shows that the solar response of the DJF temperatures in the three datasets shows large-scale similarities although there are differences over the southern middle-high latitudes and some tropical areas. The stratospheric response showed the strongest DJF temperature anomalies related to solar variability occurring over the Arctic, but its sign is negative in 1979–2002 and positive in 1958–1978. The temperature features may be partially explained by the impacts of the solar cycle, El Nino Southern Oscillation, stratospheric quasi-biennial oscillation, stratospheric aerosols, and other factors. In contrast, the tropospheric response, with a dynamic wavelike structure, occurs over the middle latitudes. The tropospheric differences between the two periods are not clearly resolved and raise questions about the efficacy of the observations and our ability to use the observations effectively.

The effect of preceding wintertime Arctic polar vortex on springtime NDVI patterns in boreal Eurasia, 1982–2015

The polar vortex is implicated in certain cold events in boreal Eurasia and has a further influence on land surface properties (e.g., vegetation and snow) during spring. The Normalized Difference Vegetation Index (NDVI) can be used as a proxy of land surface responses to climate changes to a certain degree. In this study, we demonstrate the significant correlation between preceding wintertime Arctic polar vortex intensity (WAPVI) and springtime NDVI (SNDVI) over a 34-year period (1982–2015) in boreal Eurasia (50°–75°N, 0°–150°E). Results show that a positive phase of WAPVI tends to increase the SNDVI in Europe and Lake Baikal, but causes a significant decrease in Siberia; the physical mechanisms involved in this relationship are then investigated. A positive phase of WAPVI leads to anomalies in surface air temperature and rainfall over Eurasia, which then induces a significant decrease in snow cover and snow depth in Europe and Lake Baikal and an increase of snow depth in Siberia. The colder ground temperature in Siberia during spring is considered responsible for the stronger snow depth and weaker vegetation growth in this region. The weaker and thinner snow cover in Europe and Baikal produces a decrease in albedo and an increase in heat. Thin snow melts fast in the following spring and land releases more heat to the atmosphere; consequently, warm and moist land surface facilitates vegetation growth in Europe and the Baikal regions during positive WAPVI years. In addition, WAPVI can induce sea surface temperature (SST) anomalies in the North Atlantic, which displays a tripole pattern similar to that of the empirical mode pattern in winter. Furthermore, the SST anomalous pattern persisting from winter to spring can trigger a stationary wave-train propagating from west to east in boreal Eurasia, with “negative–positive–negative–positive” geopotential height anomalies, which further exerts an impact on vegetation growth through modulation of the heat balance.

Minding the gaps: new insights into R&D management and operational transitions of NOAA satellite products

The NESDIS Center for Satellite Applications and Research (STAR), formerly ORA, Office of Research and Applications, consists of three research and applications divisions that encompass satellite meteorology, oceanography, climatology, and cooperative research with academic institutions. With such a wide background of talent, and a charter to develop operational algorithms and applications, STAR scientists develop satellite-derived land, ice, ocean, and atmospheric environmental data products in support of all of NOAA’s mission goals. In addition, in close association with the Joint Center for Satellite Data Assimilation, STAR scientists actively work with the numerical modeling communities of NOAA, NASA, and DOD to support the development of new methods for assimilation of satellite data. In this new era of observations from many new satellite instruments, STAR aims to effectively integrate these data into multi-platform data products for utilization by the forecast and applications communities. Much of our work is conducted in close partnerships with other agencies, academic institutes, and industry. In order to support the nearly 400 current satellite-derived products for various users on a routine basis from our sister operations office, and to evolve to future systems requires an ongoing strategic planning approach that maps research and development activities from NOAA goals to user requirements. Since R&D accomplishments are not necessarily amenable to precise schedules, appropriate motivators and measures of scientific progress must be developed to assure that the product development cycle remains aligned with the other engineering segments of a satellite program. This article presents the status and results of this comprehensive effort to chart a course from the present set of operational satellites to the future.

Intercomparison of the temperature contrast between the arctic and equator in the pre- and post periods of the 1976/1977 regime shift

Based on the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis temperature dataset in the period of 1948–2014, the temperature contrast between the Arctic and equator in the pre- and post periods of the 1976/1977 regime shift is compared. An index measuring the temperature contrast is defined as the difference between the Arctic zone (70° N–90° N) and the equatorial region (10° S–10° N). The variations of the temperature contrast can be mainly explained by the local sea ice variations through sea ice–albedo–temperature feedback before 1976/1977 and the energy transportation to the Arctic together with the local sea ice after 1976/1977. The impacts of the Arctic minus equator (AmE) temperature contrast on the high-level westerly jet, and the polar easterlies show a significant difference during the two periods. A strong temperature anomaly associated with the temperature contrast in the two periods is found in the high latitude, but different patterns are observed at the high and low levels. The correlated water vapor appeared in the Indian Ocean and Maritime Continent before 1976/1977 and moved to northeastern Canada and eastern North America after 1976/1977.

An Introduction to Satellite-Based Applications and Research for Understanding Climate Change

The use of satellite data in applications has changed as the environmental community has become more sophisticated deriving products from the remotely sensed measurements. This introduction summarizes the changes from the first satellites where the images were used to improve cloud forecasts to the international coordination groups that have formed to improve collaboration and data sharing of satellite observations. This introduction also addresses some of the key challenges associated with using satellite data for both weather and climate; the challenges include calibration, derived products, trend uncertainty, and measurement quality. A short discussion of subsequent future issues is briefly discussed as satellite measurement calibration reaches maturity.