Albedo-rainfall Feedback Over Indian Monsoon Region Using Long Term Observations Between 1981 to 2000

Albedo determines radiation balance of land (soil-canopy complex) surface and influence boundary layer structure of the atmosphere. Accurate surface albedo determination is important for weather forecasting, climate projection and ecosystem modelling. Albedo-rainfall feedback relationship has not been studied so far using observations on spatial scale over Indian monsoon region due to lack of consistent, systematic and simultaneous long-term measurements of both. The present study used dekadal (ten-day) composite of satellite (e.g. NOAA) based Pathfinder AVHRR Land (PAL) datasets between 1981 and 2000 over India (68–100°E, 5–40°N) at 8 km spatial resolution. Land surface albedo was computed using linear transformation of red and near infrared (NIR) surface reflectances. The cloud effects were removed using a smoothening filter with harmonic analysis applied to time series data in each year. The monthly, annual and long term means were computed from dekadal reconstructed albedo. The mean per year and coefficient of variation (CV) of surface albedo over seventeen years, averaged over Indian land region, were found to show a significantly decreasing (0.15 to 0.14 and 60 to 40%, respectively) trend between 1981 and 2000. Among all the land use patterns, the inter-annual variation of albedo of Himalayan snow cover showed a significant and the steepest reducing trend (0.42 – 0.35) followed by open shurbland, grassland and cropland. No significant change was noticed over different forest types.. This could be due to increase in snow melting period and snow melt area. A strong inverse exponential relation (correlation coefficient r = 0.95, n = 100) was found between annual rainfall and annual albedo over seven rainfall zones. The decreasing trend in snow-albedo of accumulation period (September to March) follows the declining trend in measured south-west monsoon rainfall between 1988 (980 mm) to 1998 (880 mm) over India. This finding perhaps suggests the possible reversal of reported coupling of increased snowfall followed by lower monsoon rainfall.     

Quantitative monitoring of land use changes in relation to hydrology of Bhavani basin using remote sensing techniques — a case study

The paper summarises a part of the results of an on-going project for quantifying the land use changes in Bhavani basin (Geographic co-ordinates N lat 10°55′ - 11°45′,E Long. 76°30′ - 77°45′). Landsat and aerial data have been used in monitoring the dynamic changes in land use patterns. Visually interpreted Landsat MSS data of two different dates in conjunction with the historic data acquired from the Survey of India topographic maps and field data were used in this investigation. Also land use changes over two test-sites in the basin were studied using aerial photographs. During the study, it has been observed that a direct correlation exists between the rainfall and the area irrigated. The repetitive coverage of the satellite data are found to be quite remarkable, especially the 1:250,000 False Colour Composites (FCC) in assessing rapidly the temporal land use changes of a region at a cheaper cost.     

PARASOL/POLDER3卫星数据的海洋上空云检测

在卫星海洋遥感中,云作为海气耦合系统最重要的调节器之一,其检测结果对海洋上空云微物理特性的反演精度有较大影响。因此,快速而准确识别海洋上空的云像元是卫星遥感数据处理过程中首要解决的关键问题。以PARASOL (Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar)卫星搭载的POLDER3载荷遥感数据为研究对象,提出一种改进的海洋上空云检测方法。首先剔除海洋耀光;接着利用有云与晴空区近红外反射率差异检验识别有云像元,并利用偏振反射率检验进一步识别低反射率的云像元;然后利用近红外与可见光反射率比值检验识别晴空像元;最后建立多角度云检测结果空间融合规则,重新标记有云、晴空和未定像元。以印度洋海区为例进行实验分析,将云检测结果与Buriez方法进行对比,发现检测精度基本相当,而有云像元的识别速度却平均提高约3倍。结果表明:该方法能有效的检测出海洋上空的云像元,满足业务化数据处理的高精度及时效性要求,为后续云微物理特性反演提供可靠的数据源。     

An integrated study of geospatial information technologies for surface runoff estimation in an agricultural watershed,India

Runoff is one of the important hydrologic variables used in most of the water resources applications. The Soil Conservation Service-Curve Number (SCS-CN) method is adopted for the estimation of surface runoff in the Mehadrigedda watershed area, Visakhapatnam district, India using multispectral remote sensing data, curve number approach and normal rainfall data. The main source of water in the Mehadrigedda watershed area is by rain, most of it drains off and only a little percolates into ground. The weighted curve number is determined based on antecedent moisture condition (AMC)-II with an integration of hydrologic soil groups (HSGs) and land use/land cover LULC categories. An integrated approach is applied to delineate the land use/land cover information as adopted from NRSA classification. The recording of daily rainfall data during the years 1997–2006 is collected from Indian Meteorological Department (IMD) rainguage center at Kottavalasa. It is observed that the annual rainfall-runoff relationship during 1997–2006, which is indicating that the overall increase in runoff with the rainfall of the watershed area. Integration of remote sensing (RS) and geographical infomation system (GIS) techniques provide reliable, accurate and up-to-date information on land and water resources.     

A comparison of altimeter and gravimetric geoids in the Tonga Trench and Indian Ocean areas

A gravimetric geoid computed using different techniques has been compared to a geoid derived from Geos-3 altimeter data in two 30°×30° areas: one in the Tonga Trench area and one in the Indian Ocean. The specific techniques used were the usual Stokes integration (using 1°×1° mean anomalies) with the Molodenskii truncation procedure; a modified Stokes integration with a modified truncation method; and computations using three sets of potential coefficients including one complete to degree 180. In the Tonga Trench area the standard deviation of the difference between the modified Stokes’ procedure and the altimeter geoid was ±1.1 m while in the Indian Ocean area the difference was ±0.6 m. Similar results were found from the 180×180 potential coefficient field. However, the differences in using the usual Stokes integration procedure were about a factor of two greater as was predicted from an error analysis. We conclude that there is good agreement at the ±1 m level between the two types of geoids. In addition, systematic differences are at the half-meter level. The modified Stokes procedure clearly is superior to the usual Stokes method although the 180×180 solution is of comparable accuracy with the computational effort six times less than the integration procedures.     

Landuse/Landcover change detection through remote sensing and its climatic implications in the godavari delta region

Interpretation of multi-date satellite imagery has revealed changes in land use/land cover pattern in the Godavari deltaic region during the past 26 years. The area under intensive agriculture has increased from 1459 to 3500 km² and the extent of wetland from 368 to 648 km² during the period 1973-1999, while the seasonal fallow has decreased by 2321 km². Analysis of the climatic data of 1970-1998 from different stations covering the entire 5100 km² area of the delta indicated that the day time temperatures have decreased by 0.2° C to 0.7° C, while the night time temperatures have increased by 0.5° C to 0.6° C during the past three decades. At the same time the rainfall has increased by about 75 to 479 mm. These trends in the climatic parameters arc attributed to the increased vegetation cover and wetland extent in the Godavari deltaic region.     

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.     

Impact of the Halloween 2003 ionospheric storm on kinematic GPS positioning in Europe

Using dual-frequency data from 36 GPS stations from the EUREF Permanent Network (EPN), the influence of the October 30, 2003 Halloween geomagnetic storm on kinematic GPS positioning is investigated. The Halloween storm induced ionospheric disturbances above the northern part of Europe and Scandinavia. It is shown that kinematic position repeatabilities for this period are mainly affected for stations in northern Europe with outliers reaching 12 cm in the horizontal, and 26 cm in the vertical. These magnitudes are shown to be possibly due to the second-order ionospheric delays on GPS signals, not accounted for in the kinematic GPS positioning analysis performed. In parallel, we generate hourly TEC (Total Electron Content) maps on a 1° × 1° grid using the dense EPN network. These TEC maps do not use any interpolation but provide a high resolution in the time and space and therefore allow to better evidence small structures in the ionosphere than the classical 2-hourly 2.5° × 5° grid Global Ionospheric TEC Maps (GIM). Using the hourly 1° × 1° TEC maps, we reconstruct and refine exactly the zones of intense ionosphere activity during the storm, and we show the correlation between the ionospheric activity and assess the quality of GPS-based kinematic positioning performed in the European region.     

A Case Study: Heavy Rainfall Event Comparison Between Daily Satellite Rainfall Estimation Products with IMD Gridded Rainfall Over Peninsular India During 2015 Winter Monsoon

India Meteorological department (IMD) used INSAT-3D Metrological Satellite Imager data to drive two type rainfall estimation products viz-Hydro Estimate (HE) and INSAT Multi-Spectral Rainfall Algorithm (IMSRA) on half hourly rainfall rate and daily accumulated rainfall in millimeter (mm). Integrated Multi-Satellite Retrieval for GPM (IMERG) product is being derived by NASA and JAXA by using Global Precipitation Mission (GPM) satellites data. IMSRA and GPM (IMERG) are gridded data at 10 km spatial resolution and HE is available at pixel level (4 km at Nadir). IMD provides gridded rainfall data at 0.25° × 0.25° resolution which is based on wide coverage of 6955 actual observation. In present study, validation of INSAT-3D based Hydro Estimator (HE), INSAT Multi-Spectral Rainfall Algorithm (IMSRA) and Integrated Multi-Satellite Retrieval for GPM (IMERG) of Global Precipitation Mission (GPM) satellites are carried out with IMD gridded data set for heavy rainfall event during winter monsoon, over peninsular India (November–December 2015). In validation, Nash–Sutcliffe efficiencies (NSE), RMSE, Correlation, Skilled scores are calculated at grid level for heavy and very heavy rain categories and the values of NSE of HE (? 32.36, ? 3.12), GPM (? 68.67, ? 2.39) and IMSRA (? 0.02, 0.28) on 16th November 2015 and HE (? 13.65, ? 1.69), GPM (? 43.79, ? 2.94) and IMSRA (? 1.08, ? 1.60) on 2nd Dec 2015, for heavy and very heavy rainfall. On both days, HE is showing better rainfall estimate compare to GPM for Heavy rainfall and GPM showing better estimation for very heavy rainfall events. In all the cases IMSRA is underestimating, if daily rain fall exceeded 75 mm.     

The ADV/ASV AATSR aerosol retrieval algorithm: current status and presentation of a full-mission AOD dataset

An advanced along-track scanning radiometer (AATSR) global multi-year aerosol retrieval algorithm is described. Over land, the AATSR dual-view (ADV) algorithm utilizes the measured top of the atmosphere (TOA) reflectance in both the nadir and forward views to decouple the contributions of the atmosphere and the surface to retrieve aerosol properties. Over ocean, the AATSR single-view (ASV) algorithm minimizes the discrepancy between the measured and modelled TOA reflectances in one of the views to retrieve the aerosol information using an ocean reflectance model. Necessary steps to process global, multi-year aerosol information are presented. These include cloud screening, the averaging of measured reflectance, and post-processing. Limitations of the algorithms are also discussed. The main product of the aerosol retrieval is the aerosol optical depth (AOD) at visible/near-infrared wavelengths. The retrieved AOD is validated using data from the surface-based AERONET and maritime aerosol network (MAN) sun photometer networks as references. The validation shows good agreement with the reference (r?=?0.85, RMSE?=?0.09 over land; r?=?0.83, RMSE?=?0.09 at coasts and r?=?0.96, RMSE?=?0.06 over open ocean). The results of the aerosol retrievals are presented for the full AATSR mission years 2002–2012 with seasonally averaged time series for selected regions.     

Agricultural Area Diversification and Crop Water Demand Analysis: A Remote Sensing and GIS Approach

Large scale adoption of input intensive rice–wheat cropping system in the centrally located Jalandhar district of Indian Punjab has led to over-exploitation of ground water resources, intensive use of chemical fertilizers and deterioration of soil health. To overcome these shortfalls, in the present study, agricultural area diversification plan has been generated from agricultural area and crop rotation maps derived from remote sensing data (IRS P6-AWiFS and RADARSAT ScanSAR) along with few agro-physical parameters in GIS environment. Cropping system indices (area diversity, multiple cropping and cultivated land utilization) were also worked out from remote sensing data .Analysis of remote sensing data (2004–05) revealed that rice and wheat individually remained the dominant crops, occupy 57.8% and 64.9% of total agricultural area (TAA), respectively. Therefore, in the diversified plan, it is suggested that at least 39% of the current 40% TAA under rice–wheat rotation should be replaced by other low water requiring, high value and soil enriching crops, particularly in coarse textured alluvial plain having good quality ground water zones with low annual rainfall(<700 mm). This will reduce water requirement to the tune of 15,660 cm depth while stabilizing the production and profitability by crop area diversification without further degradation of natural resources.     

基于LiDAR的农田地形环境三维重建方法

为克服传统农田土地平整测量方法耗时费力的特点,提出采用LiDAR技术对农田地形进行重建的探索性研究。通过HDL-32E型激光雷达等搭建了系统的硬件平台,应用C++语言编写了系统数据的采集程序;在此基础上对激光雷达所采集数据进行了标定,研究了农田地形重建系统中不同坐标系的转换方法;同时基于最小值去噪法设计了更适用于农田地形点云去噪的均值限差去噪法。通过对比在农田起伏较大区域不同坡度范围内RTK与激光雷达所测单元个数,对系统精度进行了评价;最后实现了车载农田地形重建系统的界面显示、应用与精度评估。结果表明,在10°~15°、25°~30°大坡度范围内激光雷达所获农田地形更为丰富,精度更高。该方法重建的农田地形模型点云数据和原始农田地形点云数据投影面积逼近度可达93%,验证了本文研究方法应用于农田地形环境重建的可行性,同时为今后的土地精细平整工作提供了理论参考与依据。     

Detailed gravimetric geoid for the North Atlantic

A detailed gravimetric geoid in the North Atlantic Ocean, named DGGNA-77, has been computed, based on a satellite and gravimetry derived earth potential model (consisting in spherical harmonic coefficients up to degree and order 30) and mean free air surface gravity anomalies (35180 1°×1° mean values and 245000 4′×4′ mean values). The long wavelength undulations were computed from the spherical harmonics of the reference potential model and the details were obtained by integrating the residual gravity anomalies through the Stokes formula: from 0 to 5° with the 4′×4′ data, and from 5° to 20° with the 1°×1° data. For computer time reasons the final grid was computed with half a degree spacing only. This grid extends from the Gulf of Mexico to the European and African coasts. Comparisons have been made with Geos 3 altimetry derived geoid heights and with the 5′×5′ gravimetric geoid derived byMarsh andChang [8] in the northwestern part of the Atlantic Ocean, which show a good agreement in most places apart from some tilts which porbably come from the satellite orbit recovery.     

Monitoring land surface albedo and vegetation dynamics using high spatial and temporal resolution synthetic time series from Landsat and the MODIS BRDF/NBAR/albedo product

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warming/cooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF/NBAR/albedo products and 30 m Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDF/Albedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30 m Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30 m albedos for the intervening daily time steps in this study. These enhanced daily 30 m spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of ±0.006. These synthetic time series provide much greater spatial detail than the 500 m gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 km by 14 km) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30 m resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.     

Locating oceanic Tuna resources in the Eastern Arabian sea using remote sensing

Tuna fishery resources are currently under exploited. The resource potential of tunas in the Indian Exclusive Economic Zone (EEZ) beyond 50 m depths is around 2.09 lakh tonnes as estimated by Fishery Survey of India. The distribution and availability of the tuna are governed by environmental factors like temperature, thermocline depth, availability of prey, visibility etc. Remote sensing provides synoptic information on productivity in terms of chlorophyll and Sea Surface Temperature (SST). In the present paper, satellite remote sensing data from Indian Remote Sensing Satellite IRS- P4 Ocean Colour Monitor (OCM) sensor for chlorophyll-a and diffuse attenuation coefficient (K) and National Oceanic and Atmospheric Administration (NOAA) - Advanced Very High Resolution Radiometer (AVHRR) sensor data for sea surface temperature were analysed and correlated within situ catch data of oceanic tunas, Skipjack(Katsuwonus pelamis) and Yellowfin tuna(Thunnus albacares), off Maharashtra coast. Higher catches were found to be associated with moderate to good primary productivity and in the vicinity of thermal fronts. Relationship between Hooking rate and SST has shown that SST of 28–30°C range is optimum for skipjack and 28–31°C for yellowfin tuna. Besides satellite derived chlorophyll and SST for identification of potential tuna fishing zones, role of diffuse attenuation coefficient (K) for visibility factor is also discussed.     

Malaria incidence in Nairobi,Kenya and dekadal trends in NDVI and climatic variables

The primary objective of this research was to determine if the remotely-sensed metric, Normalised Difference Vegetation Index (NDVI) and ground-collected dekadal climatological variables were useful predictors of future malaria outbreaks in an epidemic-prone area of Nairobi, Kenya. Data collected consisted of 36 dekadal (10-day) periods for the variables rainfall, temperature and NDVI along with yearly documented malaria admissions in 2003 for Nairobi, Kenya. Linear regression models were built for malaria cases reported in Nairobi, Kenya, as the dependent variable and various time-based groupings of temperature, rainfall and NDVI data from the dekads in both the current and the previous month as the independent variables. Data from 2003 show that malaria incidence in any given month is best predicted (R²  = 0.881, p < 0.001) by the average NDVI for the 30 days including the final two dekads of the previous month and first dekad of the current month, and by the average rainfall for the 30 days including the three dekads of rainfall data from the prior month. Forecasting an outbreak in an epidemic zone would allow public health entities to plan for and disseminate resources to the general public such as antimalarials and insecticide impregnated bed nets. In addition, vector control measures could be implemented to slow the rate of transmission in the impacted population.     

Surface Ice Flow Velocity and Tide Retrieval of the Amery Ice Shelf using Precise Point Positioning

Five days of continuous GPS observation data were collected in the frontal zone of the Amery ice shelf and subsequently post-processed using precise point position (PPP) technology based on precise orbit and clock products from the International GNSS service. The surface ice flow velocity of the observed point was derived from PPP to be 2.25 m/day toward the northeast with an azimuth of 41°. Major semi-diurnal and diurnal oceanic tide constituents could be recovered from the 5 days of PPP-derived height variations and compared well with a hydrodynamic ocean tide model. The PPP technique can replace double-difference GPS positioning in remote or hostile environments, and be used to retrieve the surface ice flow velocity without any reference station. Furthermore, the solution can be derived epoch-by-epoch with accuracy in the centimeters to decimeter range.     

Investigating the vegetation and agricultural responses to El Nino/Southern Oscillation using AVHRR data

This study explores the possible linkages of El Nino/Southern Oscillation (ENSO) with vegetation and rainfall patterns, vegetation activity and food grain yields, in arid and semi-arid regions of western India. A sequence of 20-year (1981–2000) monthly maximum Normalized Difference Vegetation Index (NDVI) data from the Advanced Very High Resolution Radiometer (AVHRR) and monthly rainfall from 160 stations were examined to study the seasonal patterns and their relation to ENSO activity. In addition, a direct (ENSO-crop yield) linkage and an intermediate (ENSO-NDVI) linkage of agricultural responses to ENSO were also investigated. The results indicate below-normal seasonal NDVI and rainfall associated with El Nino (warm) events, except during 1997, while positive anomalies occur during La Nina (cold) events. Sea surface temperature (SST) anomalies from NINO 3 region (5°N–5°S; 150°W–90°W), as an indicator of ENSO were significantly correlated with NDVI anomalies, rainfall anomalies and yield anomalies but the Southern Oscillation Index (SOI) was significantly related to NDVI anomalies only. NDVI anomaly patterns correspond to rainfall variability including that associated with ENSO activity. The observed strong intermediate linkage between yield anomalies and NDVI anomaly signal (r = 0.609) indicates that NDVI is an ideal index for understanding and analysing agricultural response to ENSO climate teleconnections.     

Effect of seasonal spectral variations on land cover classification

The supervised classification (Maximum likelihood) on three dates of IRS (LISS III) satellite data was performed to study the effect of seasonal spectral variation on land cover classification for the study area falling in the Solan district of Himachal Pradesh at latitude 30° 50’ N to 31° ’N and longitude 77° 00’ E to 77° 15’ E. It was found that the summer dataset was better with overall classification accuracy of 76% as compared to winter and spring dataset with classification accuracy of 49 and 46%, respectively.     

The determination of a one year mean sea surface height track from Geosat altimeter data and ocean variability implications

One year (November 1986 to October 1987) of Geosat altimeter data with improved orbits produced at The Ohio State University has been used to define sea surface heights for 22 ERM and one year averaged Geosat track. All sea surface heights were referenced to the single reference track through the application of geoid gradient corrections. The root mean square (RMS) gradient correction was on the order of ±1 cm although it could reach 20 cm with data points in trench areas. 10 values used to form the mean were considered. Although this study was initially driven by a need for a good reference sea surface for geodetic applications the formation of the reference track yields information on the variability of the ocean surface in the first year of the Geosat ERM. The RMS point variability was ± 12.6 cm with only a very small number of values exceeding 50 cm when a depth editing criteria was used. Global plots of the sea surface variability clearly reveal the major ocean currents and their variations in position in the year. Examination of the 1° × 1° averaged sea surface height variations show average and maximum variability values as follows: Gulf Stream (29 and 50 cm); Kurshio Current (24 and 49 cm); Agulhas Current (24 and 52 cm) and the Gulf of Mexico (18 and 31 cm). These magnitudes may be dependent on the radial orbit correction procedure. To investigate this effect sea slope variations were also computed. These results also showed clear current structures but also high frequency gravity field information despite efforts to average out such information. The data described in the paper is available from the authors for numerous other studies, some of which are suggested in the paper.