ALBERT

Description: In winter, large interannual fluctuations in the surface temperature are observed over central Europe. Comparing warm February 1990 with cold February 1996, a satellite-retrieved surface (skin) temperature difference of 9.8 K is observed for the region 50-60 degrees N; 5-35 degrees E. Previous studies show that advection from the North Atlantic constitutes the forcing to such fluctuations. The advection is quantified by Index I(sub na), the average of the ocean-surface wind speed over the eastern North Atlantic when the direction is from the southwest (when the wind is from another direction, it counts as a zero speed to the average). Average I(sub na) for February 1990 was 10.6 m/s, but for February 1996 I(sub na) was only 2.4 m/s. A large value of I(sub na) means a strong southwesterly flow which brings warm and moist air into central Europe at low level, producing a steeper tropospheric lapse rate. Strong ascending motions at 700 mb are observed in association with the occurrence of enhanced warm, moist advection from the ocean in February 1990 producing clouds and precipitation. Total precipitable water and cloud-cover fraction have larger values in February 1990 than in 1996. The difference in the greenhouse effect between these two scenarios, this reduction in heat loss to space, can be translated into a virtual radiative heating of 2.6 W/square m above the February 1990 surface/atmosphere system, which contributes to a warming of the surface on the order of 2.6 K. Accepting this estimate as quantitatively meaningful, we evaluate the direct effect, the rise in the surface temperature in Europe as a result of maritime-air inflow, as 7.2 K (9.8 K-2.6 K). Thus, fractional reinforcement by the greenhouse effect is 2.6/7.2, or 36%, a substantial positive feedback.

Description: In winter, large interannual fluctuations in the surface skin temperature are observed over central Europe: we observe a difference of 9.8 K comparing warm February 1990 with cold February 1996 for the region 50-60 degrees N; 5-35 degrees E. Previous studies show that advection from the North Atlantic constitutes the forcing to such fluctuations. The advection is quantified by Index I(sub na), the average of the ocean-surface wind speed over the eastern North Atlantic when the direction is from the southwest (when the wind is from another direction, it counts as a zero speed to the average). Average Ina for February 1990 was 10.6 in s(exp -1), but for February 1996 I(sub na) was only 2.4 m s(exp -1). A large value of I(sub na) means a strong southwesterly flow which brings warm and moist air into Europe at low level, producing a steeper tropospheric lapse rate. Strong ascending motions result, which we observe in February 1990 at 700 mb. The near-surface moisture rises to higher (and cooler) levels, producing clouds and precipitation. Total preciptable water and cloud-cover fraction have larger values in February 1990 than in 1996. The difference in the greenhouse effect between these two scenarios can be translated into a virtual irradiating source of 2.6 W m(exp -2) above the February 1990 atmosphere, which, as an order of magnitude estimate, contributes to the warming of the surface by 2.6 K. If we accept this estimate as numerically pertinent, the direct effect stands as 7.2 K (9.8 K - 2.6 K), and therefore its greenhouse-effect reinforcement is by 36%. This constitutes a substantial positive feedback to the direct effect, which is the inflow of warm air to the low troposphere over Europe.

Description: The aim of this paper is to report extreme winter/early-spring air temperature (hereinafter temperature) anomalies in mid-latitude Europe, and to discuss the underlying forcing to these interannual fluctuations. Warm advection from the North Atlantic in late winter controls the surface-air temperature, as indicated by the substantial correlation between the speed of the surface southwesterlies over the eastern North Atlantic (quantified by a specific Index Ina) and the 2-meter level air temperatures (hereinafter Ts) over Europe, 45-60 deg N, in winter. In mid-March and subsequently, the correlation drops drastically (quite often it is negative). This change in the relationship between Ts and Ina marks a transition in the control of the surface-air temperature: absorption of insolation replaces the warm advection as the dominant control. This forcing by maritime-air advection in winter was demonstrated in a previous publication, and is re-examined here in conjunction with extreme fluctuations of temperatures in Europe. We analyze here the interannual variability at its extreme by comparing warm-winter/early-spring of 1989/90 with the opposite scenario in 1995/96. For these two December-to-March periods the differences in the monthly mean temperature in Warsaw and Torun, Poland, range above 10 C. Short-term (shorter than a month) fluctuations of the temperature are likewise very strong. We conduct pentad-by-pentad analysis of the surface-maximum air temperature (hereinafter Tmax), in a selected location, examining the dependence on Ina. The increased cloudiness and higher amounts of total precipitable water, corollary effects to the warm low-level advection. in the 1989/90 winter, enhance the positive temperature anomalies. The analysis of the ocean surface winds is based on the Special Sensor Microwave/Imager (SSM/I) dataset; ascent rates, and over land wind data are from the European Centre for Medium-Range Weather Forecasts (ECMWF); maps of 2-m temperature, cloud cover and precipitable water are from the National Centers for Environmental Prediction (NCEP) Reanalysis.

Description: The Atmospheric InfraRed Sounder (AIRS), flying aboard NASA's Earth Observing System (EOS) Aqua satellite with the Advanced Microwave Sounding Unit-A (AMSU-A), has been providing data for use in numerical weather prediction (NWP) and data assimilation systems (DAS) for over three years. The full AIRS data set is currently not transmitted in near-real-time (NRT) to the NWP centers. Instead, data sets with reduced spatial and spectral information are produced and made available in NRT. In this paper, we evaluate the use of different channel selections and error specifications. We achieved significant positive impact from the Aqua AIRS/AMSU-A combination in both hemispheres during our experimental time period of January 2003. The best results were obtained using a set of 156 channels that did not include any in the 6.7micron water vapor band. The latter have a large influence on both temperature and humidity analyses. If observation and background errors are not properly specified, the partitioning of temperature and humidity information from these channels will not be correct, and this can lead to a degradation in forecast skill. We found that changing the specified channel errors had a significant effect on the amount of data that entered into the analysis as a result of quality control thresholds that are related to the errors. However, changing the channel errors within a relatively small window did not significantly impact forecast skill with the 155 channel set. We also examined the effects of different types of spatial data reduction on assimilated data sets and NWP forecast skill. Whether we picked the center or the warmest AIRS pixel in a 3x3 array affected the amount of data ingested by the analysis but had a negligible impact on the forecast skill.

Description: Scatterometer observations of the ocean surface wind speed and direction improve the depiction and prediction of storms at sea. These data are especially valuable where observations are otherwise sparse ---mostly in the Southern Hemisphere and tropics, but also on occasion in the North Atlantic and North Pacific. The SeaWinds scatterometer on the QuikScat satellite was launched in July 1999 and it represents a dramatic departure in design from the other scatterometer instruments launched during the past decade (ERS-1,2 and NSCAT). The NASA Data Assimilation Office (DAO) was the first data assimilation center to assimilate QuikScat SeaWinds data and evaluate their impact on numerical weather prediction. Several data impact experiments have been performed, using systems from both the DAO (GEOS-3) and from NCEP (GDAS). In general, these experiments have shown a modest impact of SeaWinds data on numerical weather prediction, the magnitude of which appears to be comparable to the magnitude of the impact of AMI scatterometer data from the ERS satellites. Some of the main results from these experiments will be presented at the meeting.

Description: The first SeaWinds scatterometer was launched in to space aboard the Quikscat satellite on June 19, 1999 at 7:15 p.m. PDT. Flying in a near polar orbit 800 km above the earth's surface, SeaWinds uses an advanced scatterometer design to measure surface wind velocity over 90 percent of the ice free oceans ever 24 hours. This first SeaWinds mission is designed to replace the NASA Scatterometer (NSCAT) which ceased providing wind velocity data when the ADEOS I satellite failed. A second SeaWinds is scheduled to be launched late in 2000 aboard ADEOS II. Previous scatterometer assimilation experiments conducted by the NASA Data Assimilation Office, using both ERS and NSCAT wind observations, have demonstrated considerable potential for this type of data to improve both atmospheric analyses and forecasts, however much of the smaller scale information content of the scatterometer data could not be taken into account in the early coarse resolution versions of the Goddard (GEOS) Data Assimilation System (DAS) or in operational data assimilation systems. In this paper, we will describe data assimilation experiments in which the new higher resolution versions of the GOES DAS are used to assimilate SeaWinds scatterometer winds. Following a brief discussion of the SeaWinds design and the methodology used to assimilate scatterometer data in the GOES DAS, the quality of the SeaWinds data and the impact of SeaWinds on GOES analyses and forecasts at different resolutions will be presented.