Optimized split-window coefficients for deriving surface temperatures from inland water bodies

Large inland water bodies constituting lakes, reservoirs and inland-seas are excellent proxy indicators for climate change. Using thermal infrared satellite data, a recent study found that a global set of inland water bodies showed significant warming in seasonal nighttime Lake Surface Water Temperatures (LSWTs) between 1985 and 2009. Split-window land surface temperature (LST) retrievals are typically tuned for a broad range of land surface emissivities and global atmospheric conditions, and are not optimized for inland water body surfaces, whereas split-window sea-surface temperatures (SSTs) are only tuned for a single emissivity (water), but over ocean atmospheres. Over inland water bodies, these two approaches can lead to region dependent errors in LSWTs, spurious trends, and inconsistencies between sensors in the long-term temperature record of inland water bodies. To address this issue, the primary goal of this paper was to develop a methodology for deriving a set of optimized split-window coefficients, individually tuned for the regional atmospheric conditions of 169 globally distributed, saline and freshwater inland water bodies from multiple satellite sensors including the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua; Along Track Scanning Radiometer (ATSR) including ATSR-1, ATSR-2, AATSR; and Advanced Very High Resolution Radiometer (AVHRR-3). The new Inland Water-body Surface Temperature (IWbST) v1.0 algorithm was applied to Terra MODIS and Advanced Along Track Scanning Radiometer (AATSR) data and validated with in situ water temperature data from sites with widely contrasting atmospheric conditions: Lake Tahoe in California/Nevada, a high-elevation cool and dry site, and the Salton Sea in California, a low-elevation warm and humid site. Analysis showed improved accuracy in LSWTs in terms of bias and RMSE when compared to the standard MODIS LST and AATSR SST products. For example, the IWbST RMSE at Salton Sea was reduced by 0.4 K when compared to the operational MODIS product. For the AATSR data, the IWbST RMSE was reduced by 0.36 K at Tahoe and 0.29 K at Salton Sea when compared to results obtained using the operational AATSR split-window coefficients. The IWbST improvements are significant in relation to the current accuracy of water temperature retrievals from space (< 0.5 K), and will enable the derivation of long-term, accurate LSWTs consistently across multiple sensors for climate studies.     

Multi‐scale thermal pattern monitoring of a large lake (Lake Geneva) using a multi‐sensor approach

The applicability of satellite imagery products from different sensors (AVHRR‐derived multi‐channel sea surface temperature (MCSST), MODIS sea surface temperature (SST) products 5‐Min L2 Swath 1 km and Landsat TM band 6 thermal signature) for the comprehensive monitoring of temperature and its temporal patterns over a large lake is tested in this study. The coverage of cloud‐free satellite data for Lake Geneva is reported throughout a year and, more specifically, during a 13 day period in summer 2003. In a second step, we demonstrate the feasibility of the AVHRR/MODIS imagery to discern day and night temperature patterns, by generating day and night climatologies and various spatial statistics over the 13 day period. The different day and night surface thermal patterns observed by satellite imagery could be linked to the thermal structure existing in deeper water using the concept of the diurnal decoupled layer. The forcing of the persistent patterns, two warm cores divided by a saddle‐shaped cold anomaly, is explained by wind periodicity and insolation conditions. The patterns can be matched to features postulated by findings of different limnologists in the past. Other surface temperature related phenomena such as water upwelling and downwelling and the occurrence of plumes are related to meteorological and hydrological events. The lakewide average lake surface water temperature (LSWT) trends for day and night during the study period are roughly parallel. A sudden loss of stored heat can be explained by episodes of long fetch, synoptic wind (bise) that interrupted the predominant breeze regime.     

Evolution of supra-glacial lakes across the Greenland Ice Sheet

We used 268 cloud-free Moderate-resolution Imaging Spectroradiometer (MODIS) images from 2003 and 2005-2007 to study the seasonal evolution of supra-glacial lakes in three different regions of the Greenland Ice Sheet. Lake area estimates were obtained by developing an automated classification method for their identification based on 250 m resolution MODIS surface reflectance observations. Widespread supra-glacial lake formation and drainage is observed across the ice sheet, with a 2-3 week delay in the evolution of total supra-glacial lake area in the northern areas compared to the south-west. The onset of lake growth varies by up to one month inter-annually, and lakes form and drain at progressively higher altitudes during the melt season. A positive correlation was found between the annual peak in total lake area and modelled annual runoff. High runoff and lake extent years are generally characterised by low accumulation and high melt season temperatures, and vice versa. Our results indicate that, in a future warmer climate [Meehl, G. A., Stocker, T. F., Collins W. D., Friedlingstein, P., Gaye, A. T., Gregory, J. M., Kitoh, A., Knutti, R., Murphy, J. M., Noda, A., Raper, S. C. B., Watterson, I. G., Weaver, A. J. & Zhao, Z. C. (2007). Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. B. Averyt, M. Tignor & H. L. Miller (eds.), Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.], Greenland supra-glacial lakes can be expected to form at higher altitudes and over a longer time period than is presently the case, expanding the area and time period over which connections between the ice sheet surface and base may be established [Das, S., Joughin, M., Behn, M., Howat, I., King, M., Lizarralde, D., & Bhatia, M. (2008). Fracture propagation to the base of the Greenland Ice Sheet during supra-glacial lake drainage. Science, 5877, 778-781] with potential consequences for ice sheet discharge [Zwally, H.J., Abdalati, W., Herring, T., Larson, K., Saba, J. & Steffen, K. (2002). Surface melt-induced acceleration of Greenland Ice Sheet flow. Science, 297, 218-221.].     

Hazard assessment of glacial lake outburst floods in Southeast Tibet based on RS and GIS technologies

Glacial lakes are widely distributed across glaciated mountainous regions such as Southeast Tibet (ST). As a result of climate change, glacial lakes have expanded continually in ST over recent five decades, and ST is seriously suffering from glacial lake outburst floods (GLOFs). Hence, glacial lake investigations and hazard assessments of GLOFs are very necessary to perform and are of great practical significance for this area. The region running from Ranwu to Tongmai (RTR) in ST was selected as a study area. To assess hazard degrees of GLOFs, nine factors (F1–F9) were selected from glacial characteristics: the scale of glacial lakes, meteorological conditions, moraine dam parameters and downstream gullies. Average monthly (May to September) land surface temperatures (LSTs), temperature change rates, and average annual precipitation levels were first calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) LST product and Tropical Rainfall Measuring Mission (TRMM) precipitation data. Then, glacial lake areas, downstream gully slopes, distances to glacial lakes, upper glacier areas, average gradients of upper glaciers, and terminal moraine dam widths were obtained based on Thematic Mapper (TM) and Operational Land Imager (OLI) images and Digital Elevation Model (DEM) data. Finally, the fuzzy comprehensive assessment (FCA) method was used to assess hazard degrees of GLOFs in the study area. According to the results, 135 glacial lakes existed during the study periods, five new glacial lakes formed due to lake collapse and snow and ice melt, and one disappeared due to GLOFs. The number of glacial lakes in the area increased from 130 in 1986 to 134 in 2015, and the total area of glacial lakes increased from 832.77 ha in 1986 to 850.51 ha in 2015 due to lake expansion and GLOFs. Of the 134 glacial lakes present in 2015, 10 are identified as high hazardous lakes, eight are identified as medium hazardous lakes, two are considered low hazardous lakes, and 114 are considered extremely low hazardous lakes. The results illustrate hazard levels of GLOFs in ST, which can help guide future hazard prevention in the area.     

可可西里湖泊水面面积与雪冰覆盖率相关分析

气候变化对青藏高原湖泊水面面积会产生很大的影响,雪冰覆盖作为气候变化的一个重要因素,也对青藏高原湖泊水面面积有一定的影响。利用遥感影像提取2009—2017年可可西里地区库塞湖及周边四湖(简称为四湖)的年水面面积,同时,利用2005—2016年的MODIS积雪产品,提取四湖集水区雪冰覆盖率,结合同期五道梁气象站点的逐月平均气温数据和降水量,对四湖水面面积变化与集水区雪冰覆盖变化规律及其与五道梁站气温与降水量之间的关系进行探讨。分析表明:1)卓乃湖2011年9月溃决后,4个湖泊的水面面积都发生较大的改变;2)2005—2014年期间,四湖集水区雪冰覆盖率总体呈小幅度增加趋势;3)卓乃湖溃决后,库塞湖及卓乃湖的水面面积与五道梁站年均气温的相关性显著提高,而库塞湖及卓乃湖的水面面积与四湖集水区雪冰覆盖率的相关性显著降低。     

Influence of lake morphology and clarity on water surface temperature as measured by EOS ASTER

Relationships between lake morphometric parameters and nighttime lake surface temperatures were investigated in North American temperate lakes using the ASTER kinetic temperature (AST08) product. Nighttime ASTER kinetic temperature measurements were found to be a good analogue for nighttime surface temperatures. Linear regression between ASTER and buoy-measured temperatures in a test lake were better during the evening (R² = 0.98) than the day (R² = 0.90), presumably due to the greater influence of radiation and latent heat fluxes during daylight hours. Nighttime lake surface temperatures measured in three ASTER scenes were significantly correlated to logarithm of lake area, maximum lake depth, Secchi depth (a measure of lake clarity) and lake order (a measure of lake connection with surface drainage), during October and November. Nighttime lake surface temperatures were significantly correlated only with lake area in July. We hypothesize that morphology was more strongly related to surface temperature in the fall months due to lake turnover during that season. This study suggests that satellite derived thermal data may be useful for calculation of lake heat budgets and evaporation rates, provided surface temperatures are measured in well-mixed lakes.     

Comparisons of regional satellite sea surface temperature gradients derived from MODIS and AVHRR sensors

Regional sea surface temperature (SST) gradients were examined for a 6-year (2003–2008) period using data from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua and the Advanced Very High Resolution Radiometer (AVHRR) on two NOAA satellite platforms. Two regions, one in the California Current System and the other in the Gulf Stream, representing an eastern boundary upwelling region and strong western boundary current, respectively, were chosen to investigate the seasonal variability, statistical differences and similarities, and correlations with respect to the two sets of SST gradients. Results indicated higher gradient magnitudes using MODIS SST in relative comparison to those derived from AVHRR that are attributed to instrument and algorithm differences. These observed differences are important for any studies that employ SST gradients, such as fisheries investigations that have traditionally relied on AVHRR SST gradients only.     

New refinements and validation of the MODIS Land-Surface Temperature/Emissivity products

This paper discusses the lessons learned from analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS) Land-Surface Temperature/Emissivity (LST) products in the current (V4) and previous versions, and presents eight new refinements for V5 product generation executive code (PGE16) and the test results with real Terra and Aqua MODIS data. The major refinements include considering surface elevation when using the MODIS cloudmask product, removal of temporal averaging in the 1 km daily level-3 LST product, removal of cloud-contaminated LSTs in level-3 LST products, and the refinements for the day/night LST algorithm. These refinements significantly improved the spatial coverage of LSTs, especially in highland regions, and the accuracy and stability of the MODIS LST products. Comparisons between V5 LSTs and in-situ values in 47 clear-sky cases (in the LST range from − 10 °C to 58 °C and atmospheric column water vapor range from 0.4 to 3.5 cm) indicate that the accuracy of the MODIS LST product is better than 1 K in most cases (39 out of 47) and the root of mean squares of differences is less than 0.7 K for all 47 cases or 0.5 K for all but the 8 cases apparently with heavy aerosol loadings. Emissivities retrieved by the day/night algorithm are well compared to the surface emissivity spectra measured by a sun-shadow method in two field campaigns. The time series of V5 MODIS LST product over two sites (Lake Tahoe in California and Namco lake in Tibet) in 2003 are evaluated, showing that the quantity and quality of MODIS LST products depend on clear-sky conditions because of the inherent limitation of the thermal infrared remote sensing.     

Remote sensing of the colour and temperature of volcanic lakes

Crater lakes on active volcanoes act as heat and chemical traps, and are amenable to surveillance from space. By use of all seven spectral bands, the Landsat Thematic Mapper (TM) can simultaneously measure: (i) lake surface temperature, (ii) lake surface area, and (iii) lake colour which is related to water chemistry. Use of the total instrument in this way enhances its utility for volcano surveillance. This work examines TM data for crater lakes at the following volcanoes: Ruapehu (New Zealand), Taal (Philippines), Kawah Ijen and Kelut (Indonesia), Poas (Costa Rica), and Apoyeque and Jiloa (Nicaragua). Observatory data indicate that lake surface temperatures derived by TM band 6 are typically 1-4°C less than contemporaneously measured bulk temperatures, probably due to the skin effect, the difference between water bulk and surface temperature. For Ruapehu, TM band 6 hotspots coincide approximately with known upwelling sites above volcanic vents on the lakebed. Field observations at Kawah Ijen show that the skin effect (< 3°C) is strongly correlated with windspeed: wind gusts peaking at ≈ 5m s^?1 caused rapid decreases in surface temperature of ≈ 0.5-1.0°C. These fluctuations are small compared with the magnitude of volcanogenic changes in lake temperature and do not reduce the utility of infrared surveillance. TM-derived water surface spectral reflectances indicate high concentrations of suspended chemical sediment in the most active crater lakes: Ruapehu, Poás and Ijen. For Ruapehu, imaged on two dates, the later scene reveals an upwelling slick, bright in bands 5 and 7, possibly composed of hollow sulphur spherules emitted from a subaqueous vent. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) and Enhanced Thematic Mapper (ETM +) both due for launch in 1998, will offer improved capabilities for remote surveillance of crater lakes.     

MODIS-derived surface temperature of the Great Salt Lake

The surface temperature of Utah's hypersaline Great Salt Lake is examined between 2000 and 2007 using 3345 images from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System Terra and Aqua platforms. This study shows the utility of using a multi-year record of the easily accessible and fully processed MODIS thermal imagery to monitor spatial, diurnal, seasonal, and annual variations in the surface water temperature (SWT) of lakes where long-term in situ measurements are rarely available. A cloud-free Terra image is available on average every day during the summer and early fall, every other day during spring and late fall, and every third day during the winter. MODIS-derived lake SWT exhibits a cool bias (~ − 1.5 °C) relative to in situ temperature observations gathered from three buoys and a slowly-moving watercraft.The dominant SWT signal is the annual cycle (with a range of 26 °C and peak temperature in mid-July) while the diurnal range is as large as 4 °C during the spring season. Year-to-year variations in SWT are largest during the fall with over 1 °C anomalously warm (cold) departures from the 8-year monthly medians observed during fall 2001 (2006). The MODIS imagery provides an updated SWT climatology for operational weather forecasting applications (e.g., lake-effect snow storm prediction) as well as for input into operational and research numerical weather prediction models.     

Derivation and validation of the seasonal thermal structure of Lake Malawi using multi-satellite AVHRR observations

Lake Malawi is the second largest lake in Africa by volume and an important regional source of food. Seasonal fluctuations in the primary production of the lake are principally controlled by the lake's thermal structure, which modulates the mixing of nutrient-rich deep water with that of the phytoplanktonrich near-surface layer. Satellites potentially offer an efficient, low cost method of providing information on the lakes thermal structure over the longer term via remote sensing observations of lake surface temperature. Here we investigate the accuracy of remotely sensed lake surface temperatures derived using data from the NOAA-11 AVHRR over a two-year period (1992-1993). Optimised triple window atmospheric correction algorithms are shown to provide an accuracy of around 0.5°C when compared to in situ     

Changes of Major Lakes in Central Asia and Analysis of Key Influencing Factors

The five Central Asian countries are located in the inland areas with a serious shortage of water resources and the lakes are the main support for the ecosystem in the area.Due to the lack of long-term information support both in the year and in the intervening years，it is difficult to fully understand the characteristics of the major lakes in the five Central Asian countries.In this study，MODIS 8-day reflectivity products were used as data sources from 2001 to 2016，and the Normalized Difference Water Index (NDWI) method was used to extract the water body area.The annual and inter-annual water surface of 9 major lakes in Central Asia Change Characteristics and Key Influence Factors.The results show that:(1) Lake water surface changes in the five Central Asian countries are affected by anthropogenic disturbance and climate change.The annual and interannual time series of the lake tail and alpine enclosed lake show different trend and fluctuation characteristics;(2) the changes of the Aral sea in the south and north are most obvious.The surface area of the South Aral Sea has decreased obviously in recent 15 years，reducing the area by more than 70%，while the North Aral Sea fluctuates with the variation of precipitation.(3) the total area of the sub-main lakes has been declining.The area has shrunk by 23.51% over the past 15 years.The South Aral Sea is a contributor to the statistical decrease of all lakes.However，the surface area of other lakes shows an increasing trend.     

Spatial and temporal variations of summer surface temperatures of wet polygonal tundra in Siberia - implications for MODIS LST based permafrost monitoring

The surface temperature of permafrost soils in remote arctic areas is accessible by satellite land surface temperature (LST) detection. However, the spatial resolution of satellite measurements such as the MODIS LST products is limited and does not detect the heterogeneities of the wet polygonal tundra landscape where surface wetness varies over distances of several meters. This paper examines the spatial and temporal variability of summer surface temperatures of a polygonal tundra site in northern Siberia using a ground based high resolution thermal imaging system. Thermal infrared images were taken of a 1000 m² polygonal tundra area in 10 min intervals from July to September 2008. Under clear sky conditions, the individual measurements indicate temperature differences of up to 6 K between dry and wet tundra surfaces and which can exceed 12 K when dry tundra and water surfaces are compared. These differences disappear when temperature averages are considered for intervals longer than the diurnal cycle; for weekly averages the spatial temperature variability decreases below 1 K. The exception is the free water surface of a shallow polygonal pond where weekly averaged temperature differences of 2.5 K are sustained compared to the tundra surface.The ground based thermal infrared images are upscaled to MODIS sized pixels and compared to available MODIS LST data for individual measurements and weekly averages. The comparisons show generally good agreement for the individual measurements under clear sky conditions, which exist during 20% of the studied time period. However, several erroneous measurements and large data gaps occur in the MODIS LST data during cloudy conditions, leading to biased weekly temperature averages inferred from the satellite observations. Based on these results the following recommendations are given for future permafrost temperature monitoring based on MODIS LST products: (i) high resolution surface water masks for the quality assessment in landscapes where lakes and ponds are frequent and (ii) reliable cloud cover detection in conjunction with a gap filling procedure for accurate temporal averages.     

Determination of sea surface temperature at large observation angles using an angular and emissivity-dependent split-window equation

This paper proposes an angular and emissivity-dependent split-window equation that permits the determination of the sea surface temperature (SST) to a reasonable level of accuracy for any observation angle, including large viewing angles at the image edges of satellite sensors with wide swaths. This is the case of the MODIS radiometer both on EOS Terra/Aqua platforms, with observation angles of up to 65° at the surface, for which the split-window equation has been developed in this study. The algorithm takes into account the angular dependence of both the atmospheric correction (due to the increase of the atmospheric optical path with angle) and the emissivity correction (since sea surface emissivity (SSE) decreases with observation angle). Angular-dependent coefficients have been estimated for the atmospheric terms, and also an explicit dependence on the SSE has been included in the algorithm, as this parameter has values different to a blackbody surface for off-nadir angles, the SSEs also being dependent on surface wind speed. The proposed algorithm requires as input data at-sensor brightness temperatures for the split-window bands (31 and 32 of MODIS), the observation angle at each pixel, an estimate of the water vapor content (which is provided by the MODIS MOD07/MYD07 products) and accurate SSE values for both channels. The preliminary results show a good agreement between SSTs estimated by the proposed equation for off-nadir viewings of MODIS-Terra images and in situ SST measurements, with a root-mean square error (RMSE) of about ± 0.3 K, for which the MODIS SST product gives an RMSE larger than ± 0.7 K.     

Recent trends of ice phenology for eight large lakes using MODIS products in Northeast China

Optical remote sensing images with high temporal resolution can be used to monitor lake ice phenology, a periodic freezing and thawing cycle of ice resulting from seasonal and inter-annual climate variations. In the research reported here, we used MODIS satellite data to establish the time series of lake ice extent and extracted lake ice phenology dates and durations for eight large typical lakes in Northeast China for the hydrological years from 2003 to 2016. The MODIS-derived results were validated against ice records at hydrological stations. The mean absolute error for a freeze-up start (FUS), freeze-up end (FUE), break-up start (BUS) and break-up end (BUE) was 3.1, 4.8, 6.6 and 6.6 days, respectively. Our findings indicated that the investigated lakes were tending to freeze later and melt earlier and were frozen for a shortened period over time. FUS was experiencing a delay of 0.65 days per year and BUE was advancing by 0.19 days per year, implying a decrease of frozen duration (FD) of 0.84 days per year taking all eight lakes into consideration. The lake ice duration increased with latitude, and the lakes with a relatively smaller area had a higher yearly rate of change and were more variable compared with the larger ones. The relationship between lake ice phenology and other influencing factors was evaluated using correlation coefficients and partial least squares regression. The results showed that the freeze-up process was more dependent on the lake morphometry, while the break-up process was more dependent on climate changes, particularly on air temperature, which had the highest correlation coefficient (r = ?0.69, p < 0.01).     

Analysis of leaf area index products from combination of MODIS Terra and Aqua data

A prototype product suite, containing the Terra 8-day, Aqua 8-day, Terra-Aqua combined 8- and 4-day products, was generated as part of testing for the next version (Collection 5) of the MODerate resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) products. These products were analyzed for consistency between Terra and Aqua retrievals over the following data subsets in North America: single 8-day composite over the whole continent and annual time series over three selected MODIS tiles (1200 × 1200 km). The potential for combining retrievals from the two sensors to derive improved products by reducing the impact of environmental conditions and temporal compositing period was also explored. The results suggest no significant discrepancies between large area (from continent to MODIS tile) averages of the Terra and Aqua 8-day LAI and surface reflectances products. The differences over smaller regions, however, can be large due to the random nature of residual atmospheric effects. High quality retrievals from the radiative transfer based algorithm can be expected in 90-95% of the pixels with mostly herbaceous cover and about 50-75% of the pixels with woody vegetation during the growing season. The quality of retrievals during the growing season is mostly restricted by aerosol contamination of the MODIS data. The Terra-Aqua combined 8-day product helps to minimize this effect and increases the number of high quality retrievals by 10-20% over woody vegetation. The combined 8-day product does not improve the number of high quality retrievals during the winter period because the extent of snow contamination of Terra and Aqua observations is similar. Likewise, cloud contamination in the single-sensor and combined products is also similar. The LAI magnitudes, seasonal profiles and retrieval quality in the combined 4-day product are comparable to those in the single-sensor 8-day products. Thus, the combined 4-day product doubles the temporal resolution of the seasonal cycle, which facilitates phenology monitoring in application studies during vegetation transition periods. Both Terra and Aqua LAI products show anomalous seasonality in boreal needle leaf forests, due to limitations of the radiative transfer algorithm to model seasonal variations of MODIS surface reflectance data with respect to solar zenith angle. Finally, this study suggests that further improvement of the MODIS LAI products is mainly restricted by the accuracy of the MODIS observations.     

Retrieval of high-resolution sea surface temperature data for Sendai Bay, Japan, using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)

We studied sea surface temperature (SST) retrieval algorithms for Sendai Bay, using output from the thermal-infrared channels of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on board Terra. While the highest resolutions of other satellite SST products are about 1 km, the ASTER thermal-infrared channels provide 90-m spatial resolution. To develop the ASTER algorithm, we employed statistical methods in which SSTs retrieved from the thermal-infrared measurements were tuned against the Moderate Resolution Imaging Spectroradiometer (MODIS) SST product with a 1-km spatial resolution. Terra also carries a MODIS sensor, which observed the same area as the ASTER sensor at the same time. The MODIS SST was validated around Sendai Bay, revealing a bias of −0.15 °C and root mean-square difference (RMSD) of 0.67 °C against in situ SSTs. Taking into account the spatial-resolution difference between ASTER and MODIS, match-up was generated only if the variability of ASTER brightness temperatures (T₁₃) was small in a pixel of MODIS SST (MP). The T₁₃ within one MP was about 121 pixels. The standard deviation (σ₁₃) of T₁₃ was calculated for each cloud-free MP, and the threshold of σ₁₃ for choosing match-up MPs was decided by analyzing the σ₁₃ histogram of one ASTER image. The 15 synchronous pairs of ASTER/MODIS images are separated into two groups of 8 pairs called set (A) and 7 pairs called set (B). Using the common procedure, the match-ups are generated for set (A) and set (B). The former is used for developing the ASTER Multi-Channel SST (MCSST) algorithm, and the latter for validation of the developed ASTER SST. Analysis of the whole 15 pairs indicated that ASTER SST does not depend on the satellite zenith angle. We concluded that, using Akaike's information criterion with set (A) match-ups, the multiple regression formula with all five thermal-infrared channels was adequate for the ASTER SST retrieval. Validation of ASTER SST using match-up set (B) indicated a bias of 0.101 °C and RMSD of 0.455 °C.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Monitoring lake level changes on the Tibetan Plateau using ICESat altimetry data (2003-2009)

In this study, ICESat altimetry data are used to provide precise lake elevations of the Tibetan Plateau (TP) during the period of 2003-2009. Among the 261 lakes examined ICESat data are available on 111 lakes: 74 lakes with ICESat footprints for 4-7 years and 37 lakes with footprints for 1-3 years. This is the first time that precise lake elevation data are provided for the 111 lakes. Those ICESat elevation data can be used as baselines for future changes in lake levels as well as for changes during the 2003-2009 period. It is found that in the 74 lakes (56 salt lakes) examined, 62 (i.e. 84%) of all lakes and 50 (i.e. 89%) of the salt lakes show tendency of lake level increase. The mean lake water level increase rate is 0.23 m/year for the 56 salt lakes and 0.27 m/year for the 50 salt lakes of water level increase. The largest lake level increase rate (0.80 m/year) found in this study is the lake Cedo Caka. The 74 lakes are grouped into four subareas based on geographical locations and change tendencies in lake levels. Three of the four subareas show increased lake levels. The mean lake level change rates for subareas I, II, III, IV, and the entire TP are 0.12, 0.26, 0.19, −0.11, and 0.2 m/year, respectively. These recent increases in lake level, particularly for a high percentage of salt lakes, supports accelerated glacier melting due to global warming as the most likely cause.