CEOS Land Surface Imaging Constellation Mid-Resolution Optical Guidelines

The LSI community of users is large and varied. To reach all these users as well as potential instrument contributors this document has been organized by measurement parameters of interest such as Leaf Area Index and Land Surface Temperature. These measurement parameters and the data presented in this document are drawn from multiple sources, listed at the end of the document, although the two primary ones are "The Space-Based Global Observing System in 2010 (GOS-2010)" that was compiled for the World Meteorological Organization (WMO) by Bizzarro Bizzarri, and the CEOS Missions, Instruments, and Measurements online database (CEOS MIM). For each measurement parameter the following topics will be discussed: (1) measurement description, (2) applications, (3) measurement spectral bands, and (4) example instruments and mission information. The description of each measurement parameter starts with a definition and includes a graphic displaying the relationships to four general land surface imaging user communities: vegetation, water, earth, and geo-hazards, since the LSI community of users is large and varied. The vegetation community uses LSI data to assess factors related to topics such as agriculture, forest management, crop type, chlorophyll, vegetation land cover, and leaf or canopy differences. The water community analyzes snow and lake cover, water properties such as clarity, and body of water delineation. The earth community focuses on minerals, soils, and sediments. The geo-hazards community is designed to address and aid in emergencies such as volcanic eruptions, forest fires, and large-scale damaging weather-related events

Estimation of land surface radiation budget from MODIS data

Land Surface Radiation Budget (SRB) is responsible for the available energy between the Earth and atmosphere system. Net radiation is the driving force for the transportation and exchange of all matter at the interface between the Earth's surface and the atmosphere, and therefore, significantly affects the climatic forming and change. Accurate estimation of shortwave net radiation (Sn), cloudy-sky allwave net radiation (Rn), and daily integrated Sn at high spatial resolution is essential in regional and global land surface models. The current SRB products have fine temporal and coarse spatial resolutions not suitable for land applications. New hybrid algorithm for Sn estimation has been developed in this study. Sn is estimated from MODIS data under both clear- and cloudy-sky conditions without requiring coarser resolution ancillary data. Therefore, estimated Sn retains the spatial resolution of the raw input data. Surface all-wave (both shortwave and longwave) net radiation (Rn) controls the input of latent and sensible heat flux into the atmosphere over the Earth's surface. Meteorological datasets are spatially limited and satellite data have the advantage of global spatial coverage; however, difficulty in accurately estimating cloudy-sky longwave net radiation (Ln) undermines efforts to estimate cloudy-sky all-wave net radiation. This study presents methods for estimating cloudy-sky Rn using Sn and other surface variables at 1 km spatial resolution. Daily integrated Sn is closely related to carbon, water and energy flux simulations. A daily integrated Sn product with a 1-km spatial resolution supports recent high resolution numerical climate and ecosystem simulations. This study describes a method for estimating daily integrated Sn in 1 km resolution based on instantaneous Sn data. All these algorithms have been validated using seven sites of a SURFace RADiation budget observing network (SURFRAD) in United States, instantaneous Sn is also compared with GEWEX/SRB and ISCCP data. The new hybrid algorithm developed in the study can be easily implemented to generate operational global products. These finer spatial resolution datasets capture the specific sequence of the redistribution of the available energy at the Earth's surface; therefore, they support recent high resolution land surface models