Search NASA⌕ Search

SEARCH · Search NASA

Results for “climate observations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Overview of GSICS visible calibration methods.

Global Space-based Inter-Calibration System (GSICS) is an international collaborative effort initiated in 2005 by the World Meteorological Organization (WMO) and the Coordination Group for Meteorological Satellites (CGMS) to 1-monitor, 2-improve and 3-harmonize the quality of observations from operational weather and environmental satellites of the Global Observing System (GOS). GSICS aims at ensuring consistent accuracy among space-based observations worldwide for climate monitoring, weather forecasting, and environmental applications by 1-monitoring instrument performance, 2-operational inter-calibration of satellite instruments, 3-radiometrically scaling observations to absolute reference standards, 4-recalibration of archived datasets. Although many of the GSIC visible inter-calibration methods are based on medium pixel-level imagers such as MODIS, VIIRS, AVHRR, and geostationary sensors, the methods are applicable to high spatial resolution imagery such as Landsat. For sensor inter-calibration efforts, coincident ray-matched reflectance pairs are used to transfer the calibration from the reference to the target instrument. Spectral band adjustment factors (SBAF) are applied to account for any spectral band differences. For sensor stability monitoring, PICS, deep convective cloud (DCC) and polar ice Earth viewed targets are utilized. GSICS uses the moon for stability monitoring by using the GSICS Implementation of the USGS Robotic Lunar Observatory (ROLO) model (GIRO). GSICS is looking forward to the launch of CLARREO on the international space station (ISS) in 2023. The CLARREO hyperspectral reflective solar band (RSB) sensor will establish an absolute calibration reference in space, which will characterize invariant targets and will inter-calibrate concurrent sensors. Examples of these calibration methods will be presented at the workshop.

Visible calibration methods↗
NASA NTRS2002

Science and Observation Recommendations for Future NASA Carbon Cycle Research

Between October 2000 and June 2001, an Agency-wide planning, effort was organized by elements of NASA Goddard Space Flight Center (GSFC) to define future research and technology development activities. This planning effort was conducted at the request of the Associate Administrator of the Office of Earth Science (Code Y), Dr. Ghassem Asrar, at NASA Headquarters (HQ). The primary points of contact were Dr. Mary Cleave, Deputy Associate Administrator for Advanced Planning at NASA HQ (Headquarters) and Dr. Charles McClain of the Office of Global Carbon Studies (Code 970.2) at GSFC. During this period, GSFC hosted three workshops to define the science requirements and objectives, the observational and modeling requirements to meet the science objectives, the technology development requirements, and a cost plan for both the science program and new flight projects that will be needed for new observations beyond the present or currently planned. The plan definition process was very intensive as HQ required the final presentation package by mid-June 2001. This deadline was met and the recommendations were ultimately refined and folded into a broader program plan, which also included climate modeling, aerosol observations, and science computing technology development, for contributing to the President's Climate Change Research Initiative. This technical memorandum outlines the process and recommendations made for cross-cutting carbon cycle research as presented in June. A separate NASA document outlines the budget profiles or cost analyses conducted as part of the planning effort.

McClain, Charles R.↗
NASA NTRS2021

Strong Regional Influence of Climatic Forcing Datasets on Global Crop Model Ensembles

We present results from the Agricultural Model Intercomparison and Improvement Project (AgMIP) Global Gridded Crop Model Intercomparison (GGCMI) Phase I, which aligned 14 global gridded crop models (GGCMs) and 11 climatic forcing datasets (CFDs) in order to understand how the selection of climate data affects simulated historical crop productivity of maize, wheat, rice and soybean. Results show that CFDs demonstrate mean biases and differences in the probability of extreme events, with larger uncertainty around extreme precipitation and in regions where observational data for climate and crop systems are scarce. Countries where simulations correlate highly with reported FAO national production anomalies tend to have high correlations across most CFDs, whose influence we isolate using multi-GGCM ensembles for each CFD. Correlations compare favorably with the climate signal detected in other studies, although production in many countries is not primarily climate-limited (particularly for rice). Bias-adjusted CFDs most often were among the highest model-observation correlations, although all CFDs produced the highest correlation in at least one top-producing country. Analysis of larger multi-CFD-multi-GGCM ensembles (up to 91 members) shows benefits over the use of smaller subset of models in some regions and farming systems, although bigger is not always better. Our analysis suggests that global assessments should prioritize ensembles based on multiple crop models over multiple CFDs as long as a top-performing CFD is utilized for the focus region.

Agricultural Model Intercomparison and Improvement↗
NASA NTRSDate not supplied

Development of a Consistent Cross-Platform GEO-Satellite Cloud Mask to Support CERES

Geostationary satellites provide continuous cloud and meteorological observations over a fixed portion of the Earth’s surface, allowing them to monitor the movement of storm systems and their diurnal variation. For climate studies, geostationary observations provide valuable insight of cloud formation and evolution and how they influence the Earth’s radiation budget. The Geo-Satellite Edition 4 cloud mask (GEO Ed4) is used operationally in NASA’s Cloud and Earth’s Radiant Energy System (CERES) project to help account for diurnal variations in cloudiness on Earth’s radiation budget. The Ed4 cloud mask was applied to imager data on MSG (MeteoSat Second Generation), Himawari, GOES-West, and GOES-East satellites using as much spectral information as possible. That approach led to some discontinuities when a more modern satellite replaced an older satellite with less spectral information. A different strategy is being investigated for the CERES GEO Ed5 cloud mask that only uses spectral channels common on every satellite. Thus, a 3-channel (0.6, 3.9, 11 µm) algorithm for daytime cloud detection, and a 2-channels (3.9 and 11 µm) algorithm for nighttime cloud detection have been implemented and tested for Ed5. The goal of Ed5 cloud mask is to achieve global cloud amount consistency across five geo-satellites, and a smooth transition from an old satellite to a new satellite over each geo-location. This paper compares cloud mask results between Ed4 and a preliminary Ed5 version over the GOES-East region, using GOES-8, GOES-13, and GOES-16 satellites, each with a different spectral channel complement. Instantaneous and monthly regional mean inter-comparisons are performed and evaluated with CALIPSO cloud products to assess the accuracy and consistency of the Ed5 approach relative to that taken in Ed4. Results will be presented and discussed at the conference.

clouds↗
NASA NTRS2010

Tropical Cyclones, Hurricanes, and Climate: NASA's Global Cloud-Scale Simulations and New Observations that Characterize the Lifecycle of Hurricanes

One of the primary interests of Global Change research is the impact of climate changes and climate variability on extreme weather events, such as intense tropical storms and hurricanes. Atmospheric climate models run at resolutions of global weather models have been used to study the impact of climate variability, as seen in sea surface temperatures, on the frequency and intensity of tropical cyclones. NASA's Goddard Earth Observing System Model, version 5 (GEOS-5) in ensembles run at 50 km resolution has been able to reproduce the interannual variations of tropical cyclone frequency seen in nature. This, and other global models, have found it much more difficult to reproduce the interannual changes in intensity, a result that reflects the inability of the models to simulate the intensities of the most extreme storms. Better representation of the structures of cyclones requires much higher resolution models. Such improved representation is also fundamental to making best use of satellite observations. In collaboration with NOAA's Geophysical Fluid Dynamics Laboratory, GEOS-5 now has the capability of running at much higher resolution to better represent cloud-scale resolutions. Global simulations at cloud-permitting resolutions (10- to 3.5-km) allows for the development of realistic tropical cyclones from tropical storm 119 km/hr winds) to category 5 (>249km1hr winds) intensities. GEOS-5 has produced realistic rain-band and eye-wall structures in tropical cyclones that can be directly analyzed against satellite observations. For the first time a global climate model is capable of representing realistic intensity and track variability on a seasonal scale across basins. GEOS-5 is also used in assimilation mode to test the impact of NASA's observations on tropical cyclone forecasts. One such test, for tropical cyclone Nargis in the Indian Ocean in May 2008, showed that observations from Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU-A) on Aqua substantially reduced forecast track errors. Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. SA is also bringing several state of the art instruments in recent field campaigns to peer under the clouds and study the inner workings of the tropical storms. With the Genesis and Rapid Intensification Processes (GRIP) experiment, a NASA Earth science field experiment in 2010 that includes the Global Hawk Unmanned Airborne System (UAS) configured with a suite of in situ and remote sensing instruments that are observing and characterizing the lifecycle of hurricanes, we expect significant improvement in our understanding of the track and intensification processes with the assimilation of the satellite and field campaign observations of meteorological parameters in the numerical prediction models.

Putman, William M.↗
NASA NTRS2004

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Hou, Arthur Y.↗
NASA NTRS2017

Observations of Aerosol-Radiation-Cloud Interactions in the South-East Atlantic: First Results from the ORACLES Deployments in 2016 and 2017

Southern Africa produces almost a third of the Earths biomass burning (BB) aerosol particles. Particles lofted into the mid-troposphere are transported westward over the South-East (SE) Atlantic, home to one of the three permanent subtropical stratocumulus (Sc) cloud decks in the world. The SE Atlantic stratocumulus deck interacts with the dense layers of BB aerosols that initially overlay the cloud deck, but later subside and often mix into the clouds. These interactions include adjustments to aerosol-induced solar heating and microphysical effects, and their global representation in climate models remains one of the largest uncertainties in estimates of future climate. Hence, new observations over the SE Atlantic have significant implications for regional and global climate change predictions.The low-level clouds in the SE Atlantic have limited vertical extent and therefore present favorable conditions for their exploration with remote sensing. On the other hand, the normal coexistence of BB aerosols and Sc clouds in the same scene also presents significant challenges to conventional remote sensing techniques. We describe first results from NASAs airborne ORACLES (ObseRvations of Aerosols Above Clouds and Their IntEractionS) deployments in September 2016 and August 2017. We emphasize the unique role of polarimetric observations by two instruments, the Research Scanning Polarimeter (RSP) and the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), and describe how these instruments help address specific ORACLES science objectives. Initial assessments of polarimetric observation accuracy for key cloud and aerosol properties will be presented, in as far as the preliminary nature of measurements permits.

Redemann, Jens↗
NASA NTRS2020

To What Extent Biomass Burning Aerosols Impact South America Seasonal Climate Predictions?

We applied the Goddard Earth Observing System for subseasonal to seasonal climate prediction to assess the impact of inclusion biomass burning (BB) aerosols over South America (SA) during the austral winter. We also evaluated the model sensitivity to the BB emissions prescription using no emissions, monthly climatological, and daily emissions. Each hindcast consisted of four members running from June to November of each year between 2000 and 2015. Our results indicated that interactive BB aerosols improve the seasonal climate prediction performance over SA. More realistic daily based emissions significantly further improve the performance in comparison with the climatological ones. Therefore, improvements in the BB emissions representation are urged to represent the aerosol impacts on seasonal climate prediction performance adequately.

Julliana L. M. Freire↗
NASA NTRS1981

Weather and climate

Highlights of recent progress and the directions of future advances in the application of space observations to weather and climate are reviewed. In mesometeorology and severe storms, satellite stereography of cloud topography and temperature profiling from GOES-VAS promise dramatic developments in both nowcasting and prediction. In global weather, the initial results from the year long Global Weather Experiment conclusively demonstrate the enhanced forecast skill emanating from the use of satellite data, especially cloud track winds and temperature profiles. In climate, empirical studies and numerical experiments point to the feasibility of useful climate predictions on monthly and seasonal time scales. They also indicate the kinds of surface boundary conditions to which climate is sensitive and which need to be observed from space.

Atlas, D.↗
NASA NTRS2022

Diagnosing Challenges and Setting Priorities for Sustainable Water Resource Management Under Climate Change

Managing transboundary river basins requires balancing tradeoffs of sustainable water use and coping with climate uncertainty. We demonstrate an integrated approach to exploring these issues through the lens of a social-ecological system, combining remote and in-situ earth observations, hydrologic and climate models, and social surveys. Specifically, we examine how climate change and dam development could impact the Se Kong, Se San and Sre Pok rivers in the Mekong region. We find that climate change will lead to increased precipitation, necessitating a shift in dam operations, from maintaining low flows to reducing flood hazards. We also find that existing water governance systems in Laos, Vietnam, and Cambodia are ill-prepared to address the problem. We conclude that the solution space for addressing these complex issues will be highly constrained unless major deficiencies in transboundary water governance, strategic planning, financial capacity, information sharing, and law enforcement are remedied in the next decades.

Ibrahim Nourein Mohammed↗
NASA NTRS2000

Polar Layered Deposits: Preliminary Stratigraphic Assessment from MGS Observations

Global and hemispheric climatic, volcanic and impact events that modulated the formation of the Martian polar layered deposits can be revealed by detailed stratigraphic analyses of well-exposed sequences of those layers. Complete three-dimensional Mars Orbiting Laser Altimeter (MOLA) topography of the north and south polar deposits is now available, and very abundant Mars Orbiter Camera (MOC) imagery that is well calibrated is becoming available. This paper presents an assessment of the polar stratigraphic potential based on observations from Mars Global Surveyor (MGS) mapping cycles through M7. Additional information can be found in the original extended abstract.

Murray, B. C.↗
NASA NTRS2010

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Putman, William M.↗
NASA NTRS2021

Satellite Remote Sensing to Assess Cyanobacterial Bloom Frequency Across the United States at Multiple Spatial Scales

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Imager for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.

remote sensing↗
NASA NTRS1979

A Saturnian stratospheric seasonal climate model

Motivated by recent observational evidence that seasonal processes occur within Saturn's stratosphere, a seasonal stratospheric climate model has been constructed. This model predicts stratospheric temperatures above the P = 0.1-atm level as a function of time throughout the Saturnian year. Specific results are presented for south-polar and equatorial temperatures. The model predicts that substantial seasonal phase lags exist; maximum stratospheric temperatures at the south pole occur at the southern hemisphere's autumnal equinox. Brightness temperature observations at 17.8 microns, taken during 1977/1978, indicate that stratospheric temperatures are greater at the south pole than at the equator. The model is consistent with these observations, predicting enhanced south polar temperatures, relative to the equator, from 1975 to 1983.

Cess, R. D.↗
NASA NTRS1993

The Atmospheric Impact of the 1991 Mount Pinatubo Eruption

The 1991 eruption of Pinatubo produced about 5 cubic kilometers of dacitic magma and may be the second largest volcanic eruption of the century. Eruption columns reached 40 kilometers in altitude and emplaced a giant umbrella cloud in the middle to lower stratosphere that injected about 17 megatons of SO2, slightly more than twice the largest yielded by the 1982 eruption of El Chichon, Mexico. The SO2 formed sulfate aerosols that produced the largest perturbation to the stratospheric aerosol layer since the eruption of Krakatau in 1883. The aerosol cloud spread rapidly around the Earth in about 3 weeks and attained global coverage by about 1 year after the eruption. Peak local midvisible optical depths of up to 0.4 were measured in late 1992, and globally averaged values were about 0.1 to 0.15 for 2 years. The large aerosol cloud caused dramatic decreases in the amount of net radiation reaching the Earth's surface, producing a climate forcing that was two times stronger than the aerosols of El Chichon. Effects on climate were an observed surface cooling in the northern hemisphere of up to 0.5 to 0.6 C, equivalent to a hemispheric-wide reduction in net radiation of 4 watts per square meter and a cooling of perhaps as large as -0.4 C over large parts of the earth in 1992-93. Climate models seem to have predicted the cooling with a reasonable degree of accuracy. The Pinatubo climate forcing was stronger than the opposite warming of either the El Nino event or anthropogenic greenhouse gases in the period 1991-93. As a result of the presence of the aerosol particles, midlatitude ozone concentrations reached their lowest levels on record during 1992-93, the southern hemisphere 'ozone hole' increased in 1992 to an unprecedented size and ozone depletion rates were observed to be faster than ever before recorded. The atmospheric impact of the Pinatubo eruption has been profound, and it has sparked a lively interest in the role that volcanic aerosols play in climate change. This event has shown that a powerful eruption providing a 15 to 20 megaton release of SO2 into the stratosphere can produce sufficient aerosols to offset the present global warming trends and severely impact the ozone budget.

Self, Stephen↗
NASA NTRS2014

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earth's Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulationmethods to determinemission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit.

radiometry↗
NASA NTRS2011

Retrospective Analog Year Analyses Using NASA Satellite Data to Improve USDA's World Agricultural Supply and Demand Estimates

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted, including maps, charts, and time series of recent weather, climate, and crop observations; numerical output from weather and crop models; and reports from the press, USDA attach s, and foreign governments. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. Because both the amount and timing of precipitation significantly affect crop yields, WAOB often uses precipitation time series to identify growing seasons with similar weather patterns and help estimate crop yields for the current growing season, based on observed yields in analog years. Historically, these analog years are visually identified; however, the qualitative nature of this method sometimes precludes the definitive identification of the best analog year. Thus, one goal of this study is to derive a more rigorous, statistical approach for identifying analog years, based on a modified coefficient of determination, termed the analog index (AI). A second goal is to compare the performance of AI for time series derived from surface-based observations vs. satellite-based measurements (NASA TRMM and other data).

Teng, William↗