Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. However, the climate models predict that global precipitation will increase at a much slower rate of 1 to 3% per kelvin. A recent analysis of satellite observations does not support this prediction of a muted response of precipitation to global warming. Rather, the observations suggest that precipitation and total atmospheric water have increased at about the same rate over the past two decades.
This study quantifies mean annual and monthly fluxes of Earth's water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.
The Unified Microwave Ocean Retrieval Algorithm (UMORA) simultaneously retrieves sea surface temperature, surface wind speed, columnar water vapor, columnar cloud water, and surface rain rate from a variety of passive microwave radiometers including the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). The rain component of UMORA explicitly parameterizes the three physical processes governing passive microwave rain retrievals: the beamfilling effect, cloud and rainwater partitioning, and effective rain layer thickness. Rain retrievals from the previous version of UMORA disagreed among different sensors and were too high in the tropics. These issues have been fixed with more realistic rain column heights and proper modeling of saturation and footprintresolution effects in the beamfilling correction. The purpose of this paper is to describe the rain algorithm and its recent improvements and to compare UMORA retrievals with Goddard Profiling Algorithm (GPROF) and Global Precipitation Climatology Project (GPCP) rain rates. On average, TMI retrievals from UMORA agree well with GPROF; however, large differences become apparent when the instantaneous retrievals are compared on a pixel-to-pixel basis. The differences are due to fundamental algorithm differences. For example, UMORA generally retrieves higher total liquid water, but GPROF retrieves a higher surface rain rate for a given amount of total liquid water because of differences in microphysical assumptions. Comparison of UMORA SSM/I retrievals with GPCP shows similar spatial patterns, but GPCP has higher global averages because of greater amounts of precipitation in the extratropics. UMORA and GPCP have similar linear trends over the period 1988-2005 with similar spatial patterns.
New objectively balanced observation-based reconstructions of global and continental energy budgets and their seasonal variability are presented that span the golden decade of Earth-observing satellites at the start of the twentyfirst century. In the absence of balance constraints, various combinations of modern flux datasets reveal that current estimates of net radiation into Earth's surface exceed corresponding turbulent heat fluxes by 13-24 W m 22. The largest imbalances occur over oceanic regions where the component algorithms operate independent of closure constraints. Recent uncertainty assessments suggest that these imbalances fall within anticipated error bounds for each dataset, but the systematic nature of required adjustments across different regions confirm the existence of biases in the component fluxes. To reintroduce energy and water cycle closure information lost in the development of independent flux datasets, a variational method is introduced that explicitly accounts for the relative accuracies in all component fluxes. Applying the technique to a 10-yr record of satellite observations yields new energy budget estimates that simultaneously satisfy all energy and water cycle balance constraints. , consistent with recent observations of changes in ocean heat content. Annual mean energy budgets and their seasonal cycles for each of seven continents and nine ocean basins are also presented.
Freshwater discharge from the continents is a key component of Earth's water cycle that sustains human life and ecosystem health. Surprisingly, owing to a number of socioeconomic and political obstacles, a comprehensive global river discharge observing system does not yet exist. Here we use 13 years (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) of satellite precipitation, evaporation, and sea level data in an ocean mass balance to estimate freshwater discharge into the global ocean. Results indicate that global freshwater discharge averaged 36,055 km 3 ∕y for the study period while exhibiting significant interannual variability driven primarily by El Niño Southern Oscillation cycles. The method described here can ultimately be used to estimate long-term global discharge trends as the records of sea level rise and ocean temperature lengthen. For the relatively short 13-year period studied here, global discharge increased by 540 km 3 ∕y 2 , which was largely attributed to an increase of globalocean evaporation (768 km 3 ∕y 2 ). Sustained growth of these flux rates into long-term trends would provide evidence for increasing intensity of the hydrologic cycle.climate | global water cycle | hydrology | remote sensing | observations
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