Satellite Input Research Articles

Proper depiction of monsoon depression through IRS-P4 MSMR

In this paper, daily variations of satellite-derived geophysical parameters such as integrated water vapour (IWV), cloud liquid water content (CLW), sea surface temperature (SST) and sea surface wind speed (SSW) have been studied for a case of monsoon depression that formed over the Bay of Bengal during 19th-24th August 2000. For this purpose, IRS P4 MSMR satellite data have been utilized over the domain equator — 25‡N and 40‡-100‡E. An integrated approach of satellite data obtained from IRS-P4, METEOSAT-5 and INSAT was made for getting a signal for the development of monsoon depression over the Indian region. Variations in deep convective activity obtained through visible, infrared and OLR data at 06 UTC was thoroughly analyzed for the complete life cycle of monsoon depression. Geophysical parameters obtained through IRS-P4 satellite data were compared with vorticity, convergence and divergence at 850 and 200 hPa levels generated through cloud motion vectors (CMVs) and water vapour wind vectors (WVWVs) obtained from METEOSAT-5 satellite. This comparison was made for finding proper consistency of geophysical parameters with dynamical aspects of major convective activity of the depression.From the results of this study it is revealed that there was strengthening of sea surface winds to the south of low-pressure area prior to the formation of depression. This indicated the possibility of increase in cyclonic vorticity in the lower troposphere. Hence, wind field at 850 hPa with satellite input of CMVs in objective analysis of wind field using optimum interpolation (OI) scheme was computed. Maximum cyclonic vorticity field at 850 hPa was obtained in the region of depression just one day before its formation. Similarly, with the same procedure maximum anticyclonic vorticity was observed at 200 hPa with WVWVs input. Consistent convergence and divergence at 850 and 200 hPa was noticed with respect to these vorticities. In association with these developments, we could get lowest values of OLR (120 W/m2 ) associated with major convective activity that was consistent with the maximum values of integrated water vapour (6-8gm/cm2) and cloud liquid water content (50-60 mg/cm2 ) persisting particularly in the southwest sector of the monsoon depression.

A Dual-Mode Narrow-Band Channel Filter and Group-Delay Equalizer for a Ka-Band Satellite Transponder

This paper presents the design of a narrow-band channel filter and its group-delay equalizer for a Ka-band satellite transponder. We used an 8th order channel filter for high selectivity with an elliptic-integral function response and an inline configuration. We designed a 2-pole, reflection-type, group-delay equalizer to compensate for the steep variation of the group-delay at the output of the channel filter, keeping the thermal stability at ±7 ns of group-delay variation at the band edges over 15–55 ·C. We devised a new tuning technique using short-ended dummy cavities and used it for tuning both the filter and equalizer; this removes the necessity of additional tuning after the cavities are assembled. Through measurement, we demonstrate that the group-delay-equalized filter meets the equipment requirements and is appropriate for satellite input multiplexers.

SNAの旅行・観光サテライト勘定と産業連関表

93SNAでは，従来のSNAの分析的範囲を拡大する為のサテライト勘定」という枠組みが盛り込まれました．そして改訂SNAマニュアルにおいては，文化，教育，保健・医療，社会的保護，旅行，環境保護等が例示され，米国では交通サービス，環境，鉱物資源，研究開発，旅行・観光などの分野についてサテライト勘定が作成されています．本稿ではSNAのサテライト勘定における展開と産業連関分析の新しい分野のデータ整備・分析手法の開発の関連について米国の旅行・観光産業サテライト勘定を例にあげて論じています．

Pilot study using SPOT satellite imagery over Apalachicola national forest to determine appropriate spatial scale for area-wide aggregation of surface fluxes

High resolution radiances from SPOT satellite imagery converted to Normalized Difference Vegetation Indices (NDVI) over a 16×16 km2 mixed ground cover study-area in the Apalachicola National Forest in northwest Florida, along with in situ measurements from a Bowen ratio surface flux monitoring system and physical modeling techniques, are used to determine the length manifold beyond which degraded resolution satellite imagery fails to capture flux variability over the scene. The investigation is relevant to an understanding of how bias error is generated in methods designed to produce scale-invariant surface flux estimates from satellite measurements. Error estimates are based on assigning characteristic NDVI values to the four predominant types of ground cover found within the study-area. An open site near the center of the study-area, which satisfies the conditions for surface flux monitoring, is used for obtaining input data for a biosphere-atmosphere exchange model designed to calculate representative fluxes for the different ground covers. Continuous 6-minute meteorological and surface flux measurements were made at the monitoring site for a period of 22 days. These measurements are used in conjunction with surface layer theory to provide surface layer profile estimates of wind speed, temperature, and relative humidity at the tops of the forested sites. The measured and derived meteorological parameters, together with representative biophysical parameters, are used as input to the biosphere-atmosphere exchange model. By representing sensible and latent heat flux distributions due to the variable ground cover with characteristic NDVI values at 20-m resolution, baseline area-wide sensible and latent heat flux quantities are calculated. Error-growth curves as a function of spatial resolution for the fluxes are found by degrading the resolution of the SPOT radiances used to calculate NDVI, and rationing the associated area-wide fluxes to the baseline values. The point at which an error-growth curve becomes invariant represents the edge of a length manifold beyond which the satellite input no longer contains information on surface flux variability, even though NDVI variability continues at all scales up to that of the complete SPOT scene. The error-growth curves are non-linear, with all the error build-up taking place between 20 m and 1.6 km. Decreasing the spatial resolution of the NDVI information down to or below 1.6 km, introduces bias errors in the area-wide surface flux estimates of 10% for sensible heat and 8% for latent heat. The underlying assumptions and modeling produce uncertainty in estimating the manifold limits, however, the principal objective is to show that in using satellite data for scale-invariant surface flux retrieval, there is an optimal spatial resolution factor that can be objectively quantified.

The Kansas City Flash Flood of 12 September 1977

On 12 September 1977, severe flash flooding in Kansas City, Mo., resulted in widespread damage and 25 fatalities. It was the worst flash flood of modern times in this area in terms of loss of life and damage. Meteorological analysis of the flood situation indicates the key ingredients for the unprecedented flooding were: 1) two heavy convective rain events occurring in essentially the same location within a 20 h period, and 2) the formation by the first storm system of a small-scale surface boundary wave that concentrated the low-level convergence over the Kansas City area for an extended period of time preceding the second event. Total rainfall amounts for the 24 h storm period were >16 inches (40 cm). Rainfall rates were as high as 8 inches (20 cm) in 4 h during the flooding on the evening of the 12th. Besides the conventional surface and upper air observational network, radar and satellite input were of significant value in analyzing the storm evolution.

EXPERIMENTAL USE OF SATELLITE PICTURES IN NUMERICAL PREDICTION

Errors in operational forecasts produced by high-speed electronic computers can be classed broadly into two categories: (1) those resulting from inadequacies of the dynamic model, and (2) those resulting from poor specification of the initial fields. Many regions of the Northern Hemisphere, particularly oceanic areas, are poorly observed in terms of conventional meteorological data, especially upper-air data. The SINAP (Satellite Input to Numerical Analysis and Prediction) Project at the Weather Bureau’s Meteorological Satellite Laboratory has been working to develop techniques for incorporating information derived from satellite cloud pictures into the operational numerical analysis in data-sparse areas. Trial reanalyses of the National Meteorological Center (NMC) 500-mb. stream function analysis, or its Laplacian, were performed for dataaparse areas of the central and eastern Pacific Ocean using an analysis modification technique consisting of two steps: (1) inferrinp features of the flow pattern or of the field of large-scale vertical motion from an interpretation of the TIROS-viewed cloud patterns, and (2) modifying the 500-mb. analyses to produce an appropriate vorticity advection field. Underlying this method are certain simplifying assumptions about the relation of the cloud field to the vertical motion field on the one hand, and of the vertical motion to the vorticity advection on the other. Application of the method and the results obtained are illustrated for one case. Thirty-six-hr. barotropic forecasts were run from both the original NMC analysis and the SINAP modified analysis and then compared with the verifying chart. Verification statistics, such as the root mean square (RMS) error of the stream values and of the vector geostrophic wind, are presented for the case illustrated and for five additional cases. Significant reductions in forecast error were achieved in most cases, the overall average reduction in the RMS error of the wind being 5.4 percent.