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Assessment of Geo-Kompsat-2A Atmospheric Motion Vector Data and Its Assimilation Impact in the GEOS Atmospheric Data Assimilation System

Korea’s second geostationary meteorological satellite, Geo-Kompsat-2A (Geostationary-Korean Multi-Purpose Satellite-2A, GK2A), was successfully launched on 4 December 2018. GK2Agenerates Atmospheric Motion Vectors (AMVs) every 10 min in the full disk area. This data hasbeen disseminated via Global Telecommunication System (GTS) since 25 October 2019. This articleevaluates the quality of GK2A AMVs in the Goddard Earth Observing System (GEOS) atmosphericdata assimilation system (ADAS). The data show slow wind speed biases at 200–300 hPa and 600–800hPa in the northern and southern hemispheres. These biases are caused by observation heightassignment errors near jet streams. The Equivalent Blackbody Temperature (EBBT) method of GK2Atends to assign clouds at higher altitude, which mainly causes slow wind speed biases, especially inthe lower atmosphere. The IR/WV intercept method of GK2A assigns clouds slightly lower in theatmospheric layers below the altitude of 400 hPa, which causes positive biases. Quality control (QC)criteria to select the most suitable GK2A AMV data for assimilation are presented based on thesequality assessments. A new QC criterion utilizing height errors within the GEOS ADAS is introducedto exclude data with slow wind speed biases and large errors. GEOS forecast accuracy is slightlyimproved after assimilating GK2A AMVs along with other conventional, radiance, and satellitewinds which include AMVs made by the Himawari-8 satellite in nearly the same observational areaof GK2A. Additionally, the present work shows that GEOS forecasts can be significantly improved,especially in the tropics and southern hemisphere after assimilating GK2A data in the absence ofHimawari-8 AMVs. This study demonstrates that GK2A AMV data is a valuable data source toenhance the robustness of GEOS ADAS.

Atmospheric Motion Vectors↗

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

Customer: NASA's Launch Services Program (LSP), Ground Systems Development and Operations (GSDO), and Space Launch System (SLS) programs. NASA's LSP, GSDO, SLS and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). For example, to determine if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 kilometer Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the AMU high-resolution WRF Environmental Modeling System (EMS) model (Watson 2013) in real-time. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The model was set up with a triple-nested grid configuration over KSC/CCAFS based on previous AMU work (Watson 2013). The outer domain (D01) has 12-kilometer grid spacing, the middle domain (D02) has 4-kilometer grid spacing, and the inner domain (D03) has 1.33-kilometer grid spacing. The model runs a 12-hour forecast every hour, D01 and D02 domain outputs are available once an hour and D03 is every 15 minutes during the forecast period. The AMU assessed the WRF-EMS 1.33-kilometer domain model performance for the 2014 warm season (May-September). Verification statistics were computed using the Model Evaluation Tools, which compared the model forecasts to observations. The mean error values were close to 0 and the root mean square error values were less than 1.8 for mean sea-level pressure (millibars), temperature (degrees Kelvin), dewpoint temperature (degrees Kelvin), and wind speed (per millisecond), all very small differences between the forecast and observations considering the normal magnitudes of the parameters. The precipitation forecast verification results showed consistent under-forecasting of the precipitation object size. This could be an artifact of calculating the statistics for each hour rather than for the entire 12-hour period. The AMU will continue to generate verification statistics for the 1.33-kilometer WRF-EMS domain as data become available in future cool and warm seasons. More data will produce more robust statistics and reveal a more accurate assessment of model performance. Once the formal task was complete, the AMU conducted additional work to better understand the wind direction results. The results were stratified diurnally and by wind speed to determine what effects the stratifications would have on the model wind direction verification statistics. The results are summarized in the addendum at the end of this report. In addition to verifying the model's performance, the AMU also made the output available in the Advanced Weather Interactive Processing System II (AWIPS II). This allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations AWIPS II client computers and conduct real-time subjective analyses. In the future, the AMU will implement an updated version of the WRF-EMS model that incorporates local data assimilation. This model will also run in real-time and be made available in AWIPS II.

Numerical Weather Prediction↗

Weather Research and Forecasting Model Wind Sensitivity Study at Edwards Air Force Base, CA

This abstract describes work that will be done by the Applied Meteorology Unit (AMU) in assessing the success of different model configurations in predicting "wind cycling" cases at Edwards Air Force Base, CA (EAFB), in which the wind speeds and directions oscillate among towers near the EAFB runway. The Weather Research and Forecasting (WRF) model allows users to choose among two dynamical cores - the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). There are also data assimilation analysis packages available for the initialization of the WRF model - the Local Analysis and Prediction System (LAPS) and the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS). Having a series of initialization options and WRF cores, as well as many options within each core, creates challenges for local forecasters, such as determining which configuration options are best to address specific forecast concerns. The goal of this project is to assess the different configurations available and determine which configuration will best predict surface wind speed and direction at EAFB.

Watson, Leela R.↗

Hurricane Imaging Radiometer Wind Speed and Rain Rate Retrievals during the 2010 GRIP Flight Experiment

Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes.

Sahawneh, Saleem↗

Impacts of Non-Simultaneous Global Photospheric Magnetic Measurements on Coronal and Solar Wind Modeling

The intensity and arrival time of coronal mass ejections (CMEs) can be significantly influenced by the background solar wind encountered as they propagate outward from the Sun into the interplanetary medium. In addition, solar energetic particles (SEPs) race ahead of CME shock fronts and flare regions along magnetic field lines largely determined by the background solar wind. Predicting the solar wind accurately is therefore critical for improving forecasts of CMEs, SEPs, and high-speed streams. Modeling of the corona and solar wind is challenging in general, as it is highly dependent on global photospheric magnetic field maps, which serve as the boundary conditions to all coronal models that drive solar wind models. Unfortunately, less than half of the Sun’s photospheric magnetic field is reliably measured from any given vantage point and thus it is common for the maps to have highly dated and unreliable measurements in them. While Solar Obiter (SolO) now provides for the first time the opportunity to have simultaneous measurements of nearly the entire surface magnetic field of Sun (e.g., when SolO/PHI measurements are combined with those from SDO/HMI), the required alignment to accomplish this occurs only occasionally. Further, coronal models are extremely sensitive to the strengths of the polar magnetic fields of the Sun, which remain poorly observed. Recently, efforts to mitigate this problem include using flux transport models such as the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model, which evolves the field forward in time using well known transport processes occurring on the Sun. However, it cannot account for the emergence of new magnetic flux without direct observations. The ESA VIGIL mission will eventually provide continuous observations from the L5, and the proposed SunCHASER mission will likewise do this at the L4 vantage point should it be funded. Ultimately, what is needed is a constellation of spacecraft distributed around the Sun with magnetographs that continuously measure the global surface magnetic field. In this talk, we discuss how the lack of simultaneous global measurements of the photospheric magnetic field adversely impacts the predictive performance of coronal and solar wind models.

C. Nick Arge↗

Jet stream velocity errors in general circulation models

The longitude and time dependence of excessive wind speed errors above subtropical jets in current GCM forecasts is studied for 14 five-day winter forecasts using the NASA Goddard Laboratory for Atmospheres fourth-order GCM. Several distinct phenomena, which may be divided into four categories, are found to contribute to the excess winds. These categories are: (1) error growth above the jet near the Himalayas; (2) error growth above the jet initiated elsewhere followed by advection; (3) tropical moisture bursts appearing in equatorial regions and migrating northeastward to merge with and distort the jet; and (4) undulatory growth of waves in the meridional component of the jet stream velocity. The results of additional sensitivity studies of the Himalayan region error are also reported.

Tenenbaum, J.↗

SSMI Wind Speed Climatology of the Time of Monsoon Wind Offset in the Western Arabian Sea

Forecasting the time of onset of monsoon wind in the western Arabian Sea, which is believed to precede the onset of rainfall along the west coast of India, is an important unsolved problem. Prior to measurements of the surface wind field by satellite, there was an absence of suitable surface wind observations. NASA scatterometer (NSCAT) surface wind vectors revealed that the time of the 1997 onset of 12 m/s southwest monsoon wind speeds in the western Arabian Sea preceded the onset of monsoon rainfall in Goa, India, by 3 - 4 days. Wind speed and direction data were necessary to establish a dynamical mechanism between times of onset of 12 m/s wind speed off Somalia and rainfall in Goa. Except for NSCAT, no satellite scatterometer wind product recorded adequately sampled 2-day 1deg x 1deg averaged wind vectors, which are the required space and time scales, to examine the wind-rain relationship in other years. However, the greater-than-95% steadiness of summer monsoon winds allows an opportunity to use satellite measurements of surface wind speed. The Special Sensor Microwave Imager (SSMI) recorded surface wind speed with adequate sampling to produce a 1-day, 1deg x 1deg data product during 1988 - 1998. SSMI data had been uniformly processed throughout the period. Times of onset of 12 m/s wind speed off Somalia determined with the SSMI data set were 21 May 1988, 24 May 1989, 17 May 1990, 28 May 1991, 8 June 1992, 28 May 1993, 30 May 1994, 7 June 1995, 29 May 1996, 12 June 1997, and 15 May 1998. Uncertainty of the 1992 and 1996 times of onset were increased because of the absence of SSMI data on 6 and 7 June 1992 and on 30 May 1996. Correlations of timing of monsoon wind onset with El Nino will be described. Variability of the time difference between times of onset of 12 m/s wind speed and Goa rainfall will be discussed. At the time of submission of the abstract, the Goa rainfall data have not arrived from the India Meteorological Department.

Halpern, David↗

An objective method for forecasting tropical cyclone intensity and motion using Nimbus-5 ESMR measurements and non-satellite derived descriptors

An empirical analysis program, based on finding an optimal representation of the data was applied to 120 observations of 29 1973 and 1974 North Pacific tropical cyclones. Each observation consists of a field of Nimbus-5 Electrically Scanning Microwave Radiometer radiation measurements at 267 grid points covering and surrounding the tropical cyclone plus nine other non-satellite derived discriptors. Forecast algorithms to estimate storm intensity and motion at 12, 24, 48, and 72 hours after each observation were developed using an independent eigen screening analysis. These algorithms were based on best track data. Independent testing of these algorithms showed that the performance of most of these algorithms were better than persistence and the algorithms forecasting 24, 48, and 72 hour maximum wind speed were better than those made operationally by the Joint Typhoon Warning Center for 1973 and 1974 that did not use best track data.

Hunter, H. E.↗

The String Stability of a Trajectory-Based Interval Management Algorithm in the Midterm Airspace

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides terminal controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain a precise spacing interval behind a target aircraft. As the percentage of IM equipped aircraft increases, controllers may provide IM clearances to sequences, or strings, of IM-equipped aircraft. It is important for these strings to maintain stable performance. This paper describes an analytic analysis of the string stability of the latest version of NASA's IM algorithm and a fast-time simulation designed to characterize the string performance of the IM algorithm. The analytic analysis showed that the spacing algorithm has stable poles, indicating that a spacing error perturbation will be reduced as a function of string position. The fast-time simulation investigated IM operations at two airports using constraints associated with the midterm airspace, including limited information of the target aircraft's intended speed profile and limited information of the wind forecast on the target aircraft's route. The results of the fast-time simulation demonstrated that the performance of the spacing algorithm is acceptable for strings of moderate length; however, there is some degradation in IM performance as a function of string position.

Swieringa, Kurt A.↗

Peak Wind Tool for General Forecasting

This report describes work done by the Applied Meteorology Unit (AMU) in predicting peak winds at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45th Weather Squadron requested the AMU develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. Based on observations from the KSC/CCAFS wind tower network , Shuttle Landing Facility (SLF) surface observations, and CCAFS sounding s from the cool season months of October 2002 to February 2007, the AMU created mul tiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence , the temperature inversion depth and strength, wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft.

Barrett, Joe H., III↗

Integrating Wind Profiling Radars and Radiosonde Observations with Model Point Data to Develop a Decision Support Tool to Assess Upper-Level Winds for Space Launch

On the day of launch, the 45th Weather Squadron (45 WS) Launch Weather Officers (LWOs) monitor the upper-level winds for their launch customers. During launch operations, the payload/launch team sometimes asks the LWOs if they expect the upper-level winds to change during the countdown. The LWOs used numerical weather prediction model point forecasts to provide the information, but did not have the capability to quickly retrieve or adequately display the upper-level observations and compare them directly in the same display to the model point forecasts to help them determine which model performed the best. The LWOs requested the Applied Meteorology Unit (AMU) develop a graphical user interface (GUI) that will plot upper-level wind speed and direction observations from the Cape Canaveral Air Force Station (CCAFS) Automated Meteorological Profiling System (AMPS) rawinsondes with point forecast wind profiles from the National Centers for Environmental Prediction (NCEP) North American Mesoscale (NAM), Rapid Refresh (RAP) and Global Forecast System (GFS) models to assess the performance of these models. The AMU suggested adding observations from the NASA 50 MHz wind profiler and one of the US Air Force 915 MHz wind profilers, both located near the Kennedy Space Center (KSC) Shuttle Landing Facility, to supplement the AMPS observations with more frequent upper-level profiles. Figure 1 shows a map of KSC/CCAFS with the locations of the observation sites and the model point forecasts.

Bauman, William H., III↗

Validation of Community Models: 2. Development of a Baseline, Using the Wang-Sheeley-Arge Model

This paper is the second in a series providing independent validation of community models of the outer corona and inner heliosphere. Here I present a comprehensive validation of the Wang-Sheeley-Arge (WSA) model. These results will serve as a baseline against which to compare the next generation of comparable forecasting models. The WSA model is used by a number of agencies to predict Solar wind conditions at Earth up to 4 days into the future. Given its importance to both the research and forecasting communities, it is essential that its performance be measured systematically and independently. I offer just such an independent and systematic validation. I report skill scores for the model's predictions of wind speed and interplanetary magnetic field (IMF) polarity for a large set of Carrington rotations. The model was run in all its routinely used configurations. It ingests synoptic line of sight magnetograms. For this study I generated model results for monthly magnetograms from multiple observatories, spanning the Carrington rotation range from 1650 to 2074. I compare the influence of the different magnetogram sources and performance at quiet and active times. I also consider the ability of the WSA model to forecast both sharp transitions in wind speed from slow to fast wind and reversals in the polarity of the radial component of the IMF. These results will serve as a baseline against which to compare future versions of the model as well as the current and future generation of magnetohydrodynamic models under development for forecasting use.

MacNeice, Peter↗

MiniSODAR(TradeMark) Evaluation

This report describes results of the AMU's Instrumentation and Measurement task for evaluation of the Doppler miniSODAR(TradeMark) System (DmSS). The DmSS is an acoustic wind profiler providing high resolution data to a height of approx. 410 ft. The Boeing Company installed a DmSS near Space Launch Complex 37 in mid-2002 as a substitute for a tall wind tower and plans to use DmSS data for the analysis and forecasting of winds during ground and launch operations. Peak wind speed data are of particular importance to Launch Weather Officers of the 45th Weather Squadron for evaluating user Launch Commit Criteria. The AMU performed a comparative analysis of wind data between the DmSS and nearby wind towers from August 2002 to July 2003. The DmSS vertical profile of average wind speed showed good agreement with the wind towers. However, the DMSS peak wind speeds were higher, on average, than the wind tower peak wind speeds by about 25%. A statistical model of an idealized Doppler profiler was developed and it predicted that average wind speeds would be well determined but peak wind speeds would be over-estimated due to an under-specification of vertical velocity variations in the atmosphere over the Profiler.

Short, David A.↗

First Cloud-to-Ground Lightning Timing Study

NASA's LSP, GSDO and other programs use the probability of cloud-to-ground (CG) lightning occurrence issued by the 45th Weather Squadron (45 WS) in their daily and weekly lightning probability forecasts. These organizations use this information when planning potentially hazardous outdoor activities, such as working with fuels, or rolling a vehicle to a launch pad, or whenever personnel will work outside and would be at-risk from lightning. These organizations would benefit greatly if the 45 WS could provide more accurate timing of the first CG lightning strike of the day. The Applied Meteorology Unit (AMU) has made significant improvements in forecasting the probability of lightning for the day, but forecasting the time of the first CG lightning with confidence has remained a challenge. To address this issue, the 45 WS requested the AMU to determine if flow regimes, wind speed categories, or a combination of the two could be used to forecast the timing of the first strike of the day in the Kennedy Space Center (KSC)/Cape Canaveral Air Force Station (CCAFS) lightning warning circles. The data was stratified by various sea breeze flow regimes and speed categories in the surface to 5,000-ft layer. The surface to 5,000-ft layer was selected since that is the layer the 45 WS uses to predict the behavior of sea breeze fronts, which are the dominant influence on the occurrence of first lightning in Florida during the warm season. Due to small data sample sizes after stratification, the AMU could not determine a statistical relationship between flow regimes or speed categories and the time of the first CG strike.. As expected, although the amount and timing of lightning activity varies by time of day based on the flow regimes and speed categories, there are extended tails of low lightning activity making it difficult to specify times when the threat of the first lightning flash can be avoided. However, the AMU developed a graphical user interface with input from the 45 WS that allows forecasters to visualize the climatological frequencies of the timing of the first lightning strike. This tool should contribute directly to the 45 WS goal of improving lightning timing capability for its NASA, US Air Force and commercial customers.

statistical analysis↗

Multisensor satellite data integration for sea surface wind speed and direction determination

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

Glackin, D. L.↗

Comparative analysis of operational forecasts versus actual weather conditions in airline flight planning, volume 4

The impact of more timely and accurate weather data on airline flight planning with the emphasis on fuel savings is studied. This volume of the report discusses the results of Task 4 of the four major tasks included in the study. Task 4 uses flight plan segment wind and temperature differences as indicators of dates and geographic areas for which significant forecast errors may have occurred. An in-depth analysis is then conducted for the days identified. The analysis show that significant errors occur in the operational forecast on 15 of the 33 arbitrarily selected days included in the study. Wind speeds in an area of maximum winds are underestimated by at least 20 to 25 kts. on 14 of these days. The analysis also show that there is a tendency to repeat the same forecast errors from prog to prog. Also, some perceived forecast errors from the flight plan comparisons could not be verified by visual inspection of the corresponding National Meteorological Center forecast and analyses charts, and it is likely that they are the result of weather data interpolation techniques or some other data processing procedure in the airlines' flight planning systems.

Keitz, J. F.↗

Toward the Probabilistic Forecasting of High-latitude GPS Phase Scintillation

The phase scintillation index was obtained from L1 GPS data collected with the Canadian High Arctic Ionospheric Network (CHAIN) during years of extended solar minimum 2008-2010. Phase scintillation occurs predominantly on the dayside in the cusp and in the nightside auroral oval. We set forth a probabilistic forecast method of phase scintillation in the cusp based on the arrival time of either solar wind corotating interaction regions (CIRs) or interplanetary coronal mass ejections (ICMEs). CIRs on the leading edge of high-speed streams (HSS) from coronal holes are known to cause recurrent geomagnetic and ionospheric disturbances that can be forecast one or several solar rotations in advance. Superposed epoch analysis of phase scintillation occurrence showed a sharp increase in scintillation occurrence just after the arrival of high-speed solar wind and a peak associated with weak to moderate CMEs during the solar minimum. Cumulative probability distribution functions for the phase scintillation occurrence in the cusp are obtained from statistical data for days before and after CIR and ICME arrivals. The probability curves are also specified for low and high (below and above median) values of various solar wind plasma parameters. The initial results are used to demonstrate a forecasting technique on two example periods of CIRs and ICMEs.

scintillation↗

ECMWF and SSM/I global surface wind speeds

Monthly mean 2.5 deg x 2.5 deg resolution 10-m height wind speeds from the Special Sensor Microwave/Imager (SSM/I) instrument and the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast-analysis system are compared between 60 deg S and 60 deg N during 1988-91. The SSM/I data were uniformly processed while numerous changes were made to the ECMWF forecast-analysis system. The SSM/I measurements, which were compared with moored-buoy wind observations, were used as a reference dataset to evaluate the influence of the changes made to the ECMWF system upon the ECMWF surface wind speed over the ocean. A demonstrable yearly decrease of the difference between SSM/I and ECMWF wind speeds occurred in the 10 deg S-10 deg N region, including the 5 deg S-5 deg N zone of the Pacific Ocean, where nearly all of the variations occurred in the 160 deg E-160 deg W region. The apparent improvement of the ECMWF wind speed occurred at the same time as the yearly decrease of the equatorial Pacific SSM/I wind speed, which was associated with the natural transition from La Nina to El Nino conditions. In the 10 deg S-10 deg N tropical Atlantic, the ECMWF wind speed had a 4-yr trend, which was not expected nor was it duplicated with the SSM/I data. No yearly trend was found in the difference between SSM/I and ECMWF surface wind speeds in middle latitudes of the Northern and Southern Hemispheres. The magnitude of the differences between SSM/I and ECMWF was 0.4 m/s or 100% larger in the Northern than in the Southern Hemisphere extratropics. In two areas (Arabian Sea and North Atlantic Ocean) where ECMWF and SSM/I wind speeds were compared to ship measurements, the ship data had much better agreement with the ECMWF analyses compared to SSM/I data. In the 10 deg S-10 deg N area the difference between monthly standard deviations of the daily wind speeds dropped significantly from 1988 to 1989 but remained constant at about 30% for the remaining years.

Halpern, David↗