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- Author or Editor: Taikan Oki x
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Abstract
Outputs from two ensembles of atmospheric model simulations for 1951–98 define the influence of “realistic” land surface wetness on seasonal precipitation predictability in boreal summer. The ensembles consist of one forced with observed sea surface temperatures (SSTs) and the other forced with realistic land surface wetness as well as SSTs. Predictability was determined from correlations between the time series of simulated and observed precipitation. The ratio of forced variance to total variance determined potential predictability. Predictability occurred over some land areas adjacent to tropical oceans without land wetness forcing. On the other hand, because of the chaotic nature of the atmosphere, considerable parts of the land areas of the globe did not even show potential predictability with both land wetness and SST forcings.
The use of land wetness forcing enhanced predictability over semiarid regions. Such semiarid regions are generally characterized by a negative correlation between fluxes of latent heat and sensible heat from the land surface, and are “water-regulating” areas where soil moisture plays a governing role in land–atmosphere interactions. Actual seasonal prediction may be possible in these regions if slowly varying surface conditions can be estimated in advance. In contrast, some land regions (e.g., south of the Sahel, the Amazon, and Indochina) showed little predictability despite high potential predictability. These regions are mostly characterized by a positive correlation between the surface fluxes, and are “radiation-regulating” areas where the atmosphere plays a leading role. Improvements in predictability for these regions may require further improvements in model physics.
Abstract
Outputs from two ensembles of atmospheric model simulations for 1951–98 define the influence of “realistic” land surface wetness on seasonal precipitation predictability in boreal summer. The ensembles consist of one forced with observed sea surface temperatures (SSTs) and the other forced with realistic land surface wetness as well as SSTs. Predictability was determined from correlations between the time series of simulated and observed precipitation. The ratio of forced variance to total variance determined potential predictability. Predictability occurred over some land areas adjacent to tropical oceans without land wetness forcing. On the other hand, because of the chaotic nature of the atmosphere, considerable parts of the land areas of the globe did not even show potential predictability with both land wetness and SST forcings.
The use of land wetness forcing enhanced predictability over semiarid regions. Such semiarid regions are generally characterized by a negative correlation between fluxes of latent heat and sensible heat from the land surface, and are “water-regulating” areas where soil moisture plays a governing role in land–atmosphere interactions. Actual seasonal prediction may be possible in these regions if slowly varying surface conditions can be estimated in advance. In contrast, some land regions (e.g., south of the Sahel, the Amazon, and Indochina) showed little predictability despite high potential predictability. These regions are mostly characterized by a positive correlation between the surface fluxes, and are “radiation-regulating” areas where the atmosphere plays a leading role. Improvements in predictability for these regions may require further improvements in model physics.
Abstract
A distributed biosphere hydrological (DBH) model system was used to explore the internal relations among the climate system, human society, and the hydrological system in the Yellow River basin, and to interpret possible mechanisms for observed changes in Yellow River streamflow from 1960 to 2000. Several scenarios were evaluated to elucidate the hydrological response to climate system, land cover, and irrigation. The results show that climate change is the dominant cause of annual streamflow changes in the upper and middle reaches, but human activities dominate annual streamflow changes in the lower reaches of the Yellow River basin. The annual river discharge at the mouth is affected by climate change and by human activities in nearly equal proportion. The linear component of climate change contributes to the observed annual streamflow decrease, but changes in the climate temporal pattern have a larger impact on annual river discharge than does the linear component of climate change. Low flow is more significantly affected by irrigation withdrawals than by climate change. Reservoirs induce more diversions for irrigation, while at the same time the results demonstrate that the reservoirs may help to maintain environmental flows and counter what otherwise would be more serious reductions in low flows.
Abstract
A distributed biosphere hydrological (DBH) model system was used to explore the internal relations among the climate system, human society, and the hydrological system in the Yellow River basin, and to interpret possible mechanisms for observed changes in Yellow River streamflow from 1960 to 2000. Several scenarios were evaluated to elucidate the hydrological response to climate system, land cover, and irrigation. The results show that climate change is the dominant cause of annual streamflow changes in the upper and middle reaches, but human activities dominate annual streamflow changes in the lower reaches of the Yellow River basin. The annual river discharge at the mouth is affected by climate change and by human activities in nearly equal proportion. The linear component of climate change contributes to the observed annual streamflow decrease, but changes in the climate temporal pattern have a larger impact on annual river discharge than does the linear component of climate change. Low flow is more significantly affected by irrigation withdrawals than by climate change. Reservoirs induce more diversions for irrigation, while at the same time the results demonstrate that the reservoirs may help to maintain environmental flows and counter what otherwise would be more serious reductions in low flows.
