Preliminary evaluation of the FGGE special effort for data enhancement
Man-computer Interactive Data Access System (McIDAS) terminals were utilized for data evaluation, quality assessment, and satellite data enhancement.
Engineering topics
Publications and source records attributed to Atlas, R..
Man-computer Interactive Data Access System (McIDAS) terminals were utilized for data evaluation, quality assessment, and satellite data enhancement.
The objective analysis and assimilation procedure with the FGGE/MONEX data are described. Numerical predictions with the GLAS general circulation model were made from the two initial conditions arrived at by assimilating the two different data sets. The model, the analysis and assimilation procedure, the differences in the analyses due to different data inputs, and the differences in the numerical prediction of monsoon depressions are outlined.
The statistical properties, and coverage, of satellite temperature sounding data are described. Tropical regions are observed every two days, extratropics from one to four times a day. Oceans are covered two to three times a day. Asynoptic coverage is comparable to the U.S. rawinsonde network twice daily coverage. Lack of ground truth for data sparse areas makes accuracy difficult to assess. The rms differences of layer mean temperatures obtained from collocating rawinsonde observations with satellite temperature profiles in space and time differ from rms differences of layer mean satellite temperature soundings. The FGGE satellite systems can infer the three dimensional motion field and improve the representation of the large scale state of the atmosphere.
A well defined monsoon depression was used for two assimilation and forecast experiments: (1) using conventional surface and upper air data, (2) using these data plus Monex data. The data sets were assimilated and used with a general circulation model to make numerical predictions. The model, the analysis and assimilation procedure, the differences in the analyses due to different data inputs, and the differences in the numerical predictions are described. The MONEX data have a positive impact, although the differences after 24 hr are not significant. The MONEX assimilation does not agree with manual analysis location of depression center. The 2.5 x 3 deg horizontal resolution of the prediction model is too coarse. The assimilation of geopotential height data derived from satellite soundings generated gravity waves with amplitudes similar to the meteorologically significant features investigated.
A time-continuous statistical method is presented for the four dimensional assimilation of remote sounding temperatures based on radiance measurements from polar orbiting satellites. This method is applied to DST 6 data from the NOAA 4 and Nimbus 6 satellites. The state of the atmosphere throughout the test period was determined using a varying amount of satellite data from the NOAA 4 satellite only, from Nimbus 6 only, and from both satellites together. The methods tested included different variations of the statistical method, as well as more traditional methods. It is concluded that satellite derived temperature data can have a modest, but statistically significant positive impact on numerical weather prediction in the two to three day range, and that this impact is highly sensitive to the quantity of data available and to the assimilation method used.
Attempts to improve the handling of satellite temperature and cloud-derived data during the FGGE experiment are compared with results gained during the trials. The satellite data were edited by assigning quality indicators to temperature soundings by means of the IR TV camera on the Tiros-N spacecraft, and to cloud-tracked wind data from GEO satellites. The data quality were assayed on the basis of horizontal, vertical, and temporal consistency of observed synoptic conditions. The data interpreter-operator retrieved all available data for an area, determined which regions were data-sparse, then used data-rich areas nearby to supply smoothed gradients into the zones with insufficient data. Results are presented for measurements taken during Jan.-Feb., and May 1979 over Alaska. It was found that enhanced and operational IR soundings were mostly equivalent. Some improvements were implemented in the 1000-300 mb layer thickness and intensification of atmospheric thermal gradients. Interactive processing was concluded to be an aid to processing Tiros-N data. The data-improvements treatment was found to significantly modify large scale analyses.
A special effort to produce high quality edited and enhanced global data sets is being conducted for the two special observing periods of the first GARP global experiment. More than 60 cases were selected for enhancement on the basis of meteorological interest. These cases include situations of blocking, cut off low development, cyclogenesis, and tropical circulations. The sounding data enhancement process consists of supplementing the operational satellite sounding data set with higher resolution sounding in meteorologically active regions and with new soundings where data voids or soundings of questionable quality exist. After the enhancement process is completed, a final editing and quality assessment of the enhanced data are performed. The data is archived for further analyses. Subjective evaluation of the effects of sounding data enhancement indicate that: (1) enhanced and operational IR retrievals are similar in most situations; (2) large improvements in 1000 to 300 mb thickness and mandatory level temperature and intensification of atmospheric thermal gradients occasionally occur; (3) interactive processing can fill in major gaps in the TIROS-N coverage; and (4) assimilation of special effort soundings can result in major modifications to large scale analyses and prognoses.
In January of 1978, a panel of experts recommended that a 'special effort' be made to enhance and edit satellite soundings and cloud tracked winds in data sparse regions. It was felt that these activities would be necessary to obtain maximum benefits from an evaluation of satellite data during the Global Weather Experiment (FGGE). The 'special effort' is being conducted for the two special observing periods of FGGE. More than sixty cases have been selected for enhancement on the basis of meteorological interest. These cases include situations of blocking, cutoff low development, cyclogenesis, and tropical circulations. The sounding data enhancement process consists of supplementing the operational satellite sounding data set with higher resolution soundings in meteorologically active regions, and with new soundings where data voids or soundings of questionable quality exist.
Preliminary empirical results are given of a study to determine the present-day utility of the George (1960) technique for predicting cyclogenesis. Surface and constant pressure charts are examined to determine the frequency and preferred locations for the occurrence of cold air injections. The accuracy of the empirical technique and the LFM II are compared for a limited number of cases. No consistent relationship between cold air injections and other atmospheric features is found. After the appearance of a cold air injection, cyclogenesis, a center jump, or a deepening of an existing cyclone occurs 77% of the time.
A subjective comparison of the Goddard Laboratory for Atmospheric Sciences (GLAS) and the National Meteorological Center (NMC) high resolution model forecasts is presented. Two cases where NMC's operational model in 1976 had serious difficulties in forecasting for the United States were examined. For each of the cases, the GLAS model forecasts from initial conditions which included satellite sounding data were compared directly to the NMC higher resolution model forecasts, from initial conditions which excluded the satellite data. The comparison showed that the GLAS satellite forecasts significantly improved upon the current NMC operational model's predictions in both cases.
Methods were developed for the time-continuous assimilation of satellite-sounding temperature data: direct insertion method, asynoptic successive correction method, and local linear regression method. These methods were applied to DST-6 data from the operational and experimental temperature sounders aboard the NOAA 4 and Nimbus 6 satellites. Attention is given to a comparison of these methods and their effect on the accuracy of the initial states obtained, as well as the resulting forecasts generated from these initial states. The results suggest that (1) satellite-derived temperature data can have a modest though statistically significant positive impact on numerical weather prediction in the 2-3 day range; (2) the impact is highly sensitive to the quantity of data available; and (3) the method of satellite-data assimilation can substantially influence the magnitude of the impact obtained for the same data.
Two case studies of DST-6 sounding impacts are presented. In each of these cases, major improvements to the GLAS model's forecasts of specific synoptic features resulted from including satellite-sounding data in the initial analysis.
In comparing various methods for the assimilation of remote sounding information into numerical weather prediction (NWP) models, the problem of model dependence for the different results obtained becomes important. The paper investigates two aspects of the model dependence question: (1) the effect of increasing horizontal resolution within a given model on the assimilation of sounding data, and (2) the effect of using two entirely different models with the same assimilation method and sounding data. Tentative conclusions reached are: first, that model improvement as exemplified by increased resolution, can act in the same direction as judicious 4-D assimilation of remote sounding information, to improve 2-3 day numerical weather forecasts. Second, that the time continuous 4-D methods developed at GLAS have similar beneficial effects when used in the assimilation of remote sounding information into NWP models with very different numerical and physical characteristics.
The present evaluation is concerned with (1) the significance of prognostic differences resulting from the inclusion of satellite-derived temperature soundings, (2) how specific differences between the SAT and NOSAT prognoses evolve, and (3) comparison of two experiments using the Goddard Laboratory for Atmospheric Sciences general circulation model. The subjective evaluation indicates that the beneficial impact of sounding data is enhanced with increased resolution. It is suggested that satellite sounding data posses valuable information content which at times can correct gross analysis errors in data sparse regions.
The impact of DST 5 and DST 6 satellite sounding data on mid-range forecasting was studied. The GISS temperature sounding technique, the GISS time-continuous four-dimensional assimilation procedure based on optimal statistical analysis, the GISS forecast model, and the verification techniques developed, including impact on local precipitation forecasts are described. It is found that the impact of sounding data was substantial and beneficial for the winter test period, Jan. 29 - Feb. 21. 1976. Forecasts started from initial state obtained with the aid of satellite data showed a mean improvement of about 4 points in the 48 and 772 hours Sub 1 scores as verified over North America and Europe. This corresponds to an 8 to 12 hour forecast improvement in the forecast range at 48 hours. An automated local precipitation forecast model applied to 128 cities in the United States showed on an average 15% improvement when satellite data was used for numerical forecasts. The improvement was 75% in the midwest.
A two-week prediction experiment was performed with the GISS atmospheric model on a global data set beginning 20 December 1972 to test the sensitivity of the model to sea-surface temperature (SST) variations. Use of observed SST's in place of climatological monthly mean sea temperatures for surface flux calculations in the model was found to have a marked local effect on predicted precipitation over the ocean, with enhanced convection over warm SST anomalies. However, use of observed SST's did not lead to any detectable general improvement in forecast skill. The influence of the SST anomalies on daily predicted fields of pressure and geopotential was small up to about one week compared with the growth of prediction error, and no greater over a two-week period than that resulting from random errors in the initial meteorological state. The 14-day average fields of sea-level pressure and 500 mb height predicted by the model were similarly insensitive to the SST anomalies.
The GISS model was used to compute two parallel global 30-day forecasts for the month January 1974. In one forecast, climatological January sea surface temperatures were used, while in the other observed sea temperatures were inserted and updated daily. A comparison of the two forecasts indicated no clear-cut beneficial effect of daily updating of sea surface temperatures. Despite the rapid decay of daily predictability, the model produced a 30-day mean forecast for January 1974 that was generally superior to persistence and climatology when evaluated over either the globe or the Northern Hemisphere, but not over smaller regions.
An extended range prediction experiment was performed with the GISS atmospheric model on a global data to test the sensitivity of the model to sea surface temperature (SST) variation over a two-week forecast period. The use of an initial observed SST field in place of the climatological monthly mean sea temperatures for surface flux calculations in the model was found to have a significant effect on the predicted precipitation over the ocean, with enhanced convection computed over areas where moderately large warm SST anomalies are found. However, there was no detectable positive effect of the SST anomaly field on forecast quality. The influence of the SST anomalies on the daily predicted fields of pressure and geopotential is relatively insignificant up to about one week compared with the growth of prediction error, and is no greater over a two-week period than that resulting from random errors in the initial meteorological state. The 14-day average fields of sea level pressure and 500-mb height predicted by the model, appear to be similarly insensitive to anomalies of sea surface temperature.