Snow depth estimation over north‐western Indian Himalaya using AMSR‐E

This paper presents the estimation of snow depth over north‐western Indian Himalaya using the 18.7H and 36.5H GHz channels of Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E). The Microwave Emission Model of Layered Snowpacks (MEMLS) was used along with AMSR‐E to understand the difference in the snow pack emitted and sensor received signals due to the prevailing topography. The study shows that the brightness temperature of AMSR‐E and MEMLS are comparable at 18.7 GHz with some differences in their values at 36.5 GHz showing the sensitivity of this channel to the prevailing topography.

Three years of AMSR‐E data were used to modify the 1.59 algorithm to suit the terrain and snow conditions of the north‐western Indian Himalayas. The retrieved snow depth is then compared with ground observations. Data from December to February 2003–2006 were used for the study of snow depths less than 1 m. The modified algorithm estimates the snow depth better than the old algorithm over the mountainous terrains of the north‐western Himalayas.     

Covariation in subskin‐bulk temperature difference with environmental parameters in the north Indian Ocean

This study aims to explore the dependence of the ocean subskin–bulk temperature difference ΔT (T _subskin?T _2.5m) on environmental parameters over the north Indian Ocean. This was possible because of the fortuitous concurrence of two parallel programmes, viz., the Tropical Rainfall Measuring Mission (TRMM) carrying a Microwave Imager (TMI) and the Indian moored buoy programme, over 6 years (1998–2003). The environmental parameters considered in this study are total water vapour (TWV), cloud liquid water content (CLW), sea surface wind speed, bulk temperature (T _2.5m) and T _2.5m?T _air temperature difference, consisting of a composite data matrix of more than 3000 sets. The study revealed absence of any perceptible dependence on TWV and CLW. For T _2.5m between 24°C and 28°C, the mean Δ T is a decreasing function of T _2.5m. Data classification indicates that most of the cases of T _2.5m<28°C belong to Bay of Bengal during December to February. For the T _2.5m>28°C, Δ T is very small. Our results on the variation of Δ T with T _2.5m?T _air are linear and in opposite phase. The daytime Δ T variation over the north Indian Ocean displays a decreasing trend with increasing wind. The night‐time Δ T pattern, especially over the Bay of Bengal, is found to be very unusual: it remains insensitive to the variations in wind speed, and it is predominantly positive. Diurnal variation of Δ T under wind speed below 6 m s^?1 is studied for overall data set as well as for the individual season data set. The low wind cases reproduce onset of warming at 9 h local time and a peak around 15 h local time. The average maximum amplitude of Δ T is more than 0.34°C with a standard deviation of greater than 0.7°C. Diurnal warming during pre‐monsoon (post‐monsoon) is highest (lowest).     

Comparison of SeaWiFS,MODIS‐Terra and MODIS‐Aqua in the Southern Ocean

The surface chlorophyll‐a concentrations measured by SeaWiFS, MODIS‐Terra and MODIS‐Aqua are compared in the Southern Ocean in summer 2003. The radiometers generally agree within their estimated accuracy. Residual discrepancies could be reduced by regional calibrations of the bio‐optical algorithms.     

Time-series analysis of chlorophyll-a,sea surface temperature,and sea surface height anomalies during 2003–2014 with special reference to El Niño,La Niña,and Indian Ocean Dipole (IOD) Years

The present study was carried out to find the variability of chlorophyll-a (chl-a) concentration, sea surface temperature (SST), and sea surface height anomalies (SSHa) during 2003–2014, covering the Bay of Bengal (BoB) and Arabian Sea (AS) waters. These parameters were linked with El Niño, La Niña, and Indian Ocean Dipole (IOD) years. The observed results during 2003–2014 were evaluated and it was found that the monthly mean value for 12-year data ranged as follows: chl-a (0.11–0.46 mg m^?3), SST (27–31 °C), and SSHa (?0.2 to 20 cm). The annual mean range of chl-a for 12-year data was 0.1–0.23 mg m^?3, the SST range was 27–28 °C, and the SSHa range was 2.14–13.91 cm. It has been observed that with the SST range of 27–28 °C and the SSHa range of 7–9 cm, the chl-a concentration enhanced to 0.20–0.23 mg m^?3. With a higher SST range of 28–29 °C and with a positive SSHa range of 11–14 cm, the chl-a concentration appeared to be low (0.17–0.18 mgm^?3). During normal years, SSHa was positive with the >5 to <10 cm range during the months of April–June, which coincided with an increase in SST, >2 to <4 °C. During the normal years, SSHa (>?0.2 to a concentration (>0.3 to <0.5 mg m^?3) was noticed during December–February in the BoB and AS. Compared to the BoB chl-a range (<0.4 mg m^?3), a high chl-a concentration was observed in AS (>0.4 mg m^?3). However, during the phenomenon years, the study area had experienced low chl-a (<0.2 mg m^?3), high SST (>5 °C), and more positive SSHa (>10 to <20 cm) during January–March and October–December in AS and BoB. The present study infers that a positive IOD leads to low chl-a concentration (<2 mg m^?3) and low primary productivity in AS. El Niño caused the down-welling process, it results in a low chl-a concentration (<1 mg m^?3) in BoB and AS. La Niña caused the upwelling process, and it results in a high chl-a concentration (>2.0 mg m^?3) in BoB and AS. In the recent past years (2003–2014), the intensity and frequency of El Niño, La Niña, and IOD have been increasing, evidenced with few studies, and have impacts on the Indian Ocean climate. Therefore, the influences of the relative changes of these phenomena on the BoB and AS need to be understood for productivity assessment and ocean state monitoring.     

Review Article. The sea surface thermal boundary layer and its relevance to the measurement of sea surface temperature by airborne and spaceborne radiometers†

This review examines the importance of the thermal boundary layer of the ocean to the measurement of sea surface temperature (SST) by satcllitc-bornc infrared (IR) radiometers. Attention is focused on the difference between the temperature of the top 01mm which is observed by radiometers, and the temperature found at depths between a few centimetres and one metre, which is that recorded as bulk SST by ship measurement techniques. The question addressed is whether corrections for this effect are necessary in the light of the accuracy of IR radiometers, and the demands made by the application of SST data.

A brief preview is made of the accuracy of the best presently available sensor for space observations of SST, the AVHRR, the associated atmospheric corrections and other sources of error. Current knowledge of the thermal boundary layer of the ocean is then presented in a thorough review of the scientific literature. The evidence of field observations suggests that the surface skin can be typically 0.1-0.5 degK cooler than the water a few centimetres deeper. Theoretical models of the effect are available and there is some understanding of the dependence of spatial and temporal variability of the skin effect on other environmental parameters, but there is a need for more systematic observation before prediction of the effect can confidently be achieved.

The existing and potential applications of SST in oceanography and meteorology are summarized, with emphasis on the required accuracy, in certain areas 0 2 degK being desirable. Following a survey of the likely capabilities of the next generation of spaceborne IR radiometers (notably the ATSR) it is concluded that while the inaccuracies of present systems tend to be greater than the skin effect, if future systems meet their specification then the skin temperature deviation will become a significant factor in the calibration procedure. In the light of this, the review concludes with some remarks regarding the value of further studies of the thermal skin effect.     

Fast over‐land atmospheric correction of visible and near‐infrared satellite images

A rapid atmospheric correction method is proposed to be used for visible and near‐infrared satellite sensor images over land. The method is based on a simplified use of a radiative transfer code (RTC), which is used only a priori, to generate Look‐Up‐Tables (LUTs) of the estimated surface reflectance. A typical scenario and ranges of values for the main atmospheric correction parameters are initially established. Each image pixel is treated as a slight deviation from the reference scenario defined by the vector of the typical values for the parameters. The assumption of the parameter's independence allows the use of one‐dimensional LUTs. The method is suitable for near real‐time processing or whenever a large number of data are to be handled rapidly. The operator intervention is minimal, and the computation time involved in the correction of a whole image is about 1000 times shorter than the full use of the base RTC. A test is performed with advanced very‐high‐resolution radiometer (AVHRR) visible and near‐infrared data, using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) RTC as the base code. The accuracy of the proposed method was compared with the standard use of the 6S RTC over the same dataset with resulting root mean square errors of 0.0114 and 0.0104 for AVHRR bands 1 and 2 for the estimated surface reflectance, respectively.     

Simultaneous MSMR and SSM/I observations and analysis of sea‐ice characteristics over the Antarctic region

Polar sea ice has been monitored quasi‐continuously over the last 30 years using passive microwave radiometers onboard three satellites in polar orbit, namely Nimbus‐5, Nimbus‐7 and Defense Meteorological Satellite Program (DMSP) series. A short overlap between Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus‐7 and Special Sensor Microwave Imager (SSM/I) onboard DMSP allowed inter‐calibration of the two sensors leading to a consistent series of long‐term sea‐ice measurements since 1978. With the launch of Multifrequency Scanning Microwave Radiometer (MSMR) onboard OCEANSAT‐1 in the polar sun‐synchronous orbit during 1999, India developed the capability to monitor the polar sea ice on a regular basis. The concurrent availability of SSM/I and MSMR over the last few years presents a valuable opportunity to attempt an inter‐comparison of MSMR with SSM/I measurements and derived sea‐ice parameters.

In this paper, we present an indirect validation of the brightness temperatures (T _b) observed by MSMR with near‐simultaneous measurements from SSM/I over the Antarctic and Southern Polar Ocean regions. Simultaneous MSMR and SSM/I data from two contrasting seasons—summer and winter—for the 1999–2000 period have been used. Analysis includes a comparison of T _b scatterograms to achieve confidence in the quantitative use of the T _b data to derive various geophysical parameters, e.g. sea‐ice concentration and extent. Additionally, the T _b images produced by the two sensors are compared to establish the capability of MSMR in reliable two‐dimensional portrayal of all the sea and continental ice features over the Antarctic Region. Based on a regression analysis between MSMR observed T _b in different frequency channels and polarizations, and SSM/I‐derived sea‐ice concentration (SIC) values, we have developed algorithms to estimate SIC over the Southern Polar Ocean from MSMR data. The MSMR algorithms allow estimation of SIC with better than 10% rms error. MSMR SIC images faithfully capture the observed distribution of sea ice in all the sectors of the Southern Ocean both during summer and winter periods. Using the MSMR‐derived SIC, we have also derived monthly sea‐ice extent (SIE) estimates for a period extending for about 20 months from the beginning of the launch of MSMR. These estimates show excellent agreement with values derived from SSM/I. These analyses bring out the very high level of compatibility in the measurements and derived sea‐ice parameters produced by the two sensors.     

Evaluating the performance of the space‐borne SAR sensor systems for oil spill detection and sea monitoring over the south‐eastern Mediterranean Sea

Synthetic Aperture Radar (SAR) images have been extensively used for the detection of oil spills in the marine environment as they are independent of local weather conditions, cloudiness and sun illumination. The objective of the study was to provide the users with specific knowledge on SAR image availability over a target area and assess the monitoring capability (visibility of an area) with respect to the requirements for oil‐spill detection and marine environment protection over the south‐eastern part of the Mediterranean Sea. For this purpose, a web GIS tool has been implemented, enabling the users to submit their queries and receive answers in the form of reports and statistics, concerning the current image acquisition capability over the area of interest. It also provides the user with graphic representations of the sensors' swath coverages over the same geographic location. The system has been tested over the Hellenic Seas and the resulting figures denoting the temporal resolution in the observation are analysed and discussed. The analysis shows that the operation of the Envisat satellite, in conjunction with ERS‐2 and Radarsat satellites, has significantly improved the monitoring capability. As shown, the increase in the number of observations over a target location can reach theoretically a level of 130%. In conclusion, the study provides the user with an assessment of the remaining technological gaps and unmet user needs in the domain of marine environment protection.     

Inter-comparing and improving land surface temperature estimates from passive microwaves over the Jiangsu province of the People’s Republic of China

In the recent years, the FengYun-3B passive microwave observations (FY3B) have been used to study global and regional soil moisture estimates, and land surface temperature (LST) has been an important input in the retrieval model. Previous studies proposed a linear model to derive LST from Ka-band brightness temperatures (H09 approach) which were routinely masked based on open water data. This study aimed to further understand microwave emission under such challenging open water conditions and developed the first data-driven approach to correct for such open water conditions. The H09 was first applied to the FY3B observations, and then inter-compared against MODIS (Moderate-resolution Imaging Spectro-radiometer), MERRA (Modern Era Retrospective analysis for Research and Applications) and ground observations over the Jiangsu province in the People’s Republic of China. Several freshwater bodies are located within this region, and the Pacific Ocean bounds at the east, this makes it an excellent region for the study of open water impact on the passive microwave observations. As in previous studies, the quality of the FY3B LST based on the H09 approach dropped over the regions with high open water. While the MERRA and MODIS LST products maintained an average correlation of about 0.95, the FY3B LST product had an average correlation of 0.85 with drops to about 0.65 over the open water regions. Additional comparisons also revealed biases over the open water regions within the passive microwave product. An open water metric, which is based on the percentage of a pixel and its surrounding pixels covered by water was developed to quantify the impact of open water. Based on a pixel-wise linear relationship between the MERRA LST and FY3B Ka-band brightness temperature, spatially variable slopes and intercepts were obtained as a function of open water to produce a correction for open water in the H09 which leads to the HG18 approach. Validations with both the MODIS LST product and the ground observations showed that there was a significant reduction in both the absolute bias (MODIS: 2 K, in situ: 10 K) and the standard errors (MODIS: 0.8 K, in situ: 1 K) using the HG18 approach. This opens up a new window towards further improving and understanding LST retrievals from passive microwave products.     

Retrieval of land and sea surface temperature using NOAA-11 AVHRR· data in north-eastern Brazil

The split-window method is investigated and a simple airborne atmospheric correction model for thermal data is proposed. Analysis shows that the atmospheric transmittance has a quadratic behaviour with the water vapour content in the first few kilometres of a wet atmosphere. The effect of the emissivity is evaluated for the retrieval of surface temperature using data from NOAA-11 AVHRR channels 4 and 5 for two extreme atmospheres. The results indicate that a spectral emissivity variation (Δε) in channels 4 and 5 of ±0.01 is not as important for a wet atmosphere as for a dry atmosphere. The split-window algorithm developed in this work has its parameters dependent on the atmospheric state and the values of these parameters are determined by using radiosonde profiles. Data from eighty-five radiosondes have been used to determine and check the local seasonal equatorial split-window parameters. The results of surface temperature retrieval show that the local seasonal equatorial and daily split-window parameters (given by daily radiosonde profiles) for NOAA-11 AVHRR data exhibit good agreement between their surface temperature results and the results of in situ measurements for two days. Comparisons with in situ measurements show that the maximum difference from retrieving a vegetated surface temperature using AVHRR data is less than 1.0°C in a wet atmosphere. Although the seasonal parameters have demonstrated a good performance when applied for two particular days, it does not indicate that they can be used successfully for other times when the atmospheric state differs from the average seasonal profile determined in this work. Evidence of this fact is shown through the variation of water vapour amount in the eighty-five radiosonde atmospheric profiles that have been analysed. This variation presents a wide range in water vapour from 2.8g cm^-2, to 4.92g cm^-2, which can significantly modify the retrieval of surface temperature using remote infrared sensors. Discussion of this problem is given in this paper.     

Mean seasonal cycle and evolution of the sea surface temperature from satellite and in situ data in the English Channel for the period 1986–2006

A night-time series of sea surface temperature (SST) of the advanced very high-resolution radiometer (AVHRR) sensors provided by the AVHRR/Pathfinder was analysed over the period 1986–2006 in the English Channel. The studied area is characterized by a strong influence of the bathymetry on the mixing of the water column, mostly through the action of the tide and waves, leading to regional patterns in the SST fields. Another specific aspect of the area is the relatively large number of in situ measurements available from coastal stations. The remotely sensed SST data with fine spatial resolution and high-frequency measurements made at coastal stations have been analysed using a common model. The long-term evolution of SST has been defined in this study through a linear trend while the seasonal evolution has been described through two harmonic functions. The daily satellite SST fields have been estimated over the period 1986–2006 by applying the kriging method to the anomalies calculated from the model. These interpolated temperatures were compared with in situ data, including many coastal stations unreachable at the sensor resolution. To use those coastal stations for comparison and to complement the satellite-derived data set, we defined transfer functions established from fine analysis of the in situ gradients along cross shore transects. The study showed the existence of a long-term warming and that this trend was not homogeneous in the area studied. The central part of the English Channel and the Western part of Brittany show an increase in temperature of about 0.6°C and the Northern part of the Irish and Baltic Sea, included in the studied area, show a maximum increase in the temperature of 1.6°C over the period 1986–2006.     

Comparison of the RF MEMS switches with dielectric layers on the bridge’s lower surface and on the transmission line

Previously, we proposed that the dielectric layer of RF MEMS switch can be fabricated either on the transmission line, as traditional switches, or on the lower surface of the bridge. This paper presents a detailed comparison of the RF MEMS switches with different positions of dielectric layer. Through theoretically analyzing the physical model of fringing capacitance, it is revealed that different positions of dielectric layer can result in different switch capacitances. Therefore, the change of d...     

The effect of orbit drift on the calibration of the 3.7 µm channel of the AVHRR onboard NOAA-14 and its impact on night-time sea surface temperature retrievals

The orbit drift of National Oceanic & Atmospheric Administration (NOAA)-14 towards the terminator has caused the deterioration of the radiometric calibration of the Advanced Very High Resolution Radiometer (AVHRR) 3.7?µm channel at night. This deterioration is a result of solar contamination of the radiometric calibration system when the sun strikes the instrument from the spacecraft horizon. The long-term trend and seasonal variation of the contamination are analysed in this study based on trending data from 1995 to 2000. The calibration bias is evaluated and its effect on the sea surface temperature retrievals is quantified. The solar contamination in late 2000 affected as much as 25% of an orbit of data, compared to an average of 7% in 1995. The NOAA/NESDIS operational calibration algorithm partially corrects for the bias but residual effects can still contribute bias on the order of 0.5?K in scene brightness temperature.     

On the use of synthetic 12 μm data in a split-window retrieval of sea surface temperature from AVHRR measurements

A numerical model of the radiation transfer through the atmosphere is used with a set of mid-latitude atmospheric profiles to simulate split-window measurements of the AVHRR/2 on the NOAA-7 satellite. These are used to quantify the degradation in accuracy which results in going from a sea surface temperature retrieval in which the effect of the atmosphere is estimated using measurements at 11 μm and 12 μm (channels 4 and 5), to one in which it is estimated using synthetic channel 5 data, as advocated by Singh et al (1985).     

On identification of wakes and trails at sea with IRS‐P4 OCM data

Ship wakes and aircraft contrails were identified in the IRS‐P4 OCM data. The ship wake signatures were analysed for the observations made in shipping corridors of the Persian Gulf on 3 June 1999 and in the of the Arabian Sea on 17 February 2000. While the aircraft contrails were studied with OCM data on 17 November 1999 off Mumbai, India and 18 February 2002 in the Arabian Sea. The study of wakes and trails helped discriminating ships and aircraft location at the sea.     

Assessing the potential to derive air–sea freshwater fluxes from Aquarius‐like observations of surface salinity

A state‐of‐the‐art numerical model is used to investigate the possibility of determining freshwater flux fields from temporal changes in sea‐surface salinity (SSS), a goal of the satellite salinity‐measuring mission, Aquarius/SAC‐D. Because the estimated advective temporal scale is usually longer than the Aquarius/SAC‐D revisit time, the possibility of producing freshwater flux estimates from temporal salinity changes is first examined by using a correlation analysis. For the mean seasonal cycle, the patterns of the correlations between the freshwater fluxes and surface salinity temporal tendencies are mainly zonally oriented, and are highest where the local precipitation is also relatively high. Nonseasonal (deviations from the monthly mean) correlations are highest along mid‐latitude storm tracks and are relatively small in the tropics. The complex correlation patterns presented here suggest that a global retrieval of the difference between evaporation and precipitation (E–P) from salinity changes requires more complex techniques than a simple consideration of a local balance with surface forcing.     

Interannual variability of convective activity over the tropical Indian Ocean during the El Niño/La Niña events

Convection over the tropical Indian Ocean is important to the global and regional climate. This study presents the monthly climatology of convection, inferred from the outgoing longwave radiation (OLR), over the tropical Indian Ocean. We also examine the impact of El Niño/La Niña events on the convection pattern and how variations in convection over the domain influence the spatial rainfall distribution over India. We used 35 recent years (1974–2008) of satellite-derived OLR over the area, the occurrence of El Niño/La Niña events and high resolution grid point rainfall data over India. The most prominent feature of the annual cycle of OLR over the domain is the movements of convection from south-east to north and north-west during the winter to the summer monsoon season. This feature represents the movement of the inter-tropical convergence zone (ITCZ). The climatology of OLR during the winter months (December–February) over the domain is characterized by high subsidence over central India with a decrease of OLR values towards the north and south. Moderate convection is also seen over the Himalayan Range and the south-east Indian Ocean. In contrast, during the summer (June–September) the OLR pattern indicates deep convection along the monsoon trough and over central India, with subsidence over the extreme north-west desert region. The annual march of convection over the Arabian Sea and Bay of Bengal sector shows that the Arabian Sea has a limited role, compared to the Bay of Bengal, in the annual cycle of the convection over the tropical Indian Ocean. The composite OLR anomalies for the El Niño cases during the summer monsoon season show suppressed convection over all of India and moderate convection over the central equatorial Indian Ocean and over the northern part of the Bay of Bengal. Meanwhile in La Niña events the OLR pattern is nearly opposite to the El Niño case, with deep convection over entire Indian region and adjoining seas and subsidence over the northern Bay of Bengal and extreme north-west region. The spatial variability of the 1°?×?1° summer monsoon rainfall data over India is also examined during El Niño/La Niña events. The results show that rainfall of the summer monsoon season over the southern peninsular of India and some parts of central India are badly affected during El Niño cases, while the region lying along the monsoon trough and the west coast of India have received good amounts of rainfall. This spatial seasonal summer monsoon rainfall distribution pattern seems to average out the influence of El Niño events on total summer monsoon rainfall over India. It seems that, in El Niño events, the convection pattern over the Bay of Bengal remains unaffected during summer monsoon months and thus this region plays an important role in giving good summer monsoon rainfall over the northern part of India, which dilutes the influence of El Niño on seasonal scale summer monsoon rainfall over India. These results are also confirmed by using a monthly bias-corrected OLR dataset.     

Evaluation and improvement of the MODIS land surface temperature/emissivity products using ground‐based measurements at a semi‐desert site on the western Tibetan Plateau

Current MODerate‐resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST, surface skin temperature)/emissivity products are evaluated and improvements are investigated. The ground‐based measurements of LST at Gaize (32.30° N, 84.06° E, 4420 m) on the western Tibetan Plateau from January 2001 to December 2002 agree well (mean and standard deviation of differences of 0.27 K and 0.84 K) with the 1‐km Version 004 (V4) Terra MODIS LST product (MOD11A1) generated by the split‐window algorithm. Spectral emissivities measured from surface soil samples collected at and around the Gaize site are in close agreement with the landcover‐based emissivities in bands 31 and 32 used by the split‐window algorithm. The LSTs in the V4 MODIS LST/emissivity products (MYD11B1 for Aqua and MOD11B1 for Terra) from the day/night LST algorithm are higher by 1–1.7 K (standard deviation around 0.6 K) in comparisons to the 5‐km grid aggregated values of the LSTs in the 1‐km products, which is consistent with the results of a comparison of emissivities. On average, the emissivity in MYD11B1 (MOD11B1) is 0.0107 (0.0167) less than the ground‐based measurements, which is equivalent to a 0.64 K (1.25 K) overestimation of LST around the average value of 285 K. Knowledge obtained from the evaluation of MODIS LST/emissivity retrievals provides useful information for the improvement of the MODIS LST day/night algorithm. Improved performance of the refined (V5) day/night algorithm was demonstrated with the Terra MODIS data in May–June 2004.