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Abstract
The diurnal cycle of precipitation is investigated using ground-based hourly observations for more than 10 years both in Japan and Malaysia. The diurnal cycle of precipitation in Japan is classified into three clusters. The first one has a peak in the morning, and the stations categorized into this cluster are located in coastal regions. The second cluster has two peaks in the morning and in the evening. These stations are located in an inland region. The morning peak in the above two clusters is dominant in June, when it is “baiu” in Japan. Baiu is the rainy season related to the southwest Asian monsoon. The third cluster is an exceptional case. No morning peak is observed in the stations of the third cluster and they have a comparatively strong evening peak.
In the case of the Malay Peninsula, the inland region has a pronounced peak of rainfall at 1600 LST; the magnitude exceeds the mean of each month by 200%. This evening peak is too sharp to be represented by a 24-h-cycle sine wave decomposed by Fourier transform. The intensity also becomes higher at the peak time (1500 LST). The magnitude of the diurnal cycle of mean intensity is larger than the annual cycle of monthly mean intensity. The morning peak of precipitation is observed during the southwest monsoon season on the west coast, and during the northeast monsoon season on the east coast. The intensity of precipitation is not significantly high during this period; namely, the increase of the probability or the duration of precipitation forms this morning peak. These evidences indicate the mechanism of the convective rainfall by the thermodynamic forcing in the evening, and the low-level convergence between the local land–sea breeze and the predominant monsoon wind in the morning.
Abstract
The diurnal cycle of precipitation is investigated using ground-based hourly observations for more than 10 years both in Japan and Malaysia. The diurnal cycle of precipitation in Japan is classified into three clusters. The first one has a peak in the morning, and the stations categorized into this cluster are located in coastal regions. The second cluster has two peaks in the morning and in the evening. These stations are located in an inland region. The morning peak in the above two clusters is dominant in June, when it is “baiu” in Japan. Baiu is the rainy season related to the southwest Asian monsoon. The third cluster is an exceptional case. No morning peak is observed in the stations of the third cluster and they have a comparatively strong evening peak.
In the case of the Malay Peninsula, the inland region has a pronounced peak of rainfall at 1600 LST; the magnitude exceeds the mean of each month by 200%. This evening peak is too sharp to be represented by a 24-h-cycle sine wave decomposed by Fourier transform. The intensity also becomes higher at the peak time (1500 LST). The magnitude of the diurnal cycle of mean intensity is larger than the annual cycle of monthly mean intensity. The morning peak of precipitation is observed during the southwest monsoon season on the west coast, and during the northeast monsoon season on the east coast. The intensity of precipitation is not significantly high during this period; namely, the increase of the probability or the duration of precipitation forms this morning peak. These evidences indicate the mechanism of the convective rainfall by the thermodynamic forcing in the evening, and the low-level convergence between the local land–sea breeze and the predominant monsoon wind in the morning.
Abstract
A normalized difference vegetation index (NDVI) cloud index (NCI) was derived from Pathfinder Advanced Very High Resolution Radiometer (AVHRR) daily NDVI data and compared with observed cloud amounts and a sunshine duration–cloud index (SCI) over an area of diverse land cover. Ground observations from 120 meteorological stations were significantly related to the daily NCI and the SCI, with R 2 values of 0.41 and 0.50, respectively. The daily NCI and interpolated cloud indices derived from ground observations over the 776 900 km2 study area were compared. The correlation coefficient between the NCI and the observed cloud amount was less than 0.6 for less than 20% of the area. The correlation coefficient between the NCI and the observed sunshine duration index was less than 0.6 for less than 10% of the area and less than 0.7 for 41% of the area. There were strong correlations for high elevations in summer, and correlations for low elevations in winter were weaker. A frozen soil surface or snow cover degrades the NDVI relationship to clouds. The NCI and observed cloud indices had high correlation coefficients in areas with diverse land uses, suggesting that the NCI may be useful in estimating cloudiness over a large region.
Abstract
A normalized difference vegetation index (NDVI) cloud index (NCI) was derived from Pathfinder Advanced Very High Resolution Radiometer (AVHRR) daily NDVI data and compared with observed cloud amounts and a sunshine duration–cloud index (SCI) over an area of diverse land cover. Ground observations from 120 meteorological stations were significantly related to the daily NCI and the SCI, with R 2 values of 0.41 and 0.50, respectively. The daily NCI and interpolated cloud indices derived from ground observations over the 776 900 km2 study area were compared. The correlation coefficient between the NCI and the observed cloud amount was less than 0.6 for less than 20% of the area. The correlation coefficient between the NCI and the observed sunshine duration index was less than 0.6 for less than 10% of the area and less than 0.7 for 41% of the area. There were strong correlations for high elevations in summer, and correlations for low elevations in winter were weaker. A frozen soil surface or snow cover degrades the NDVI relationship to clouds. The NCI and observed cloud indices had high correlation coefficients in areas with diverse land uses, suggesting that the NCI may be useful in estimating cloudiness over a large region.
Abstract
A dense tipping-bucket rain gauge network was established in the Mae Chaem watershed in the mountains of northwestern Thailand as part of the Global Energy and Water Cycle Experiment (GEWEX) Asian Monsoon Experiment-Tropics (GAME-T). Investigations of rainfall amounts, intensities, durations, and frequencies in the rainy season revealed strong orographic rainfall enhancement in the region. The larger amount of high-altitude rainfall was attributed to duration and frequency rather than intensity. Despite large rainfall variations, similar patterns were found in the two study years, 1998 and 1999.
Abstract
A dense tipping-bucket rain gauge network was established in the Mae Chaem watershed in the mountains of northwestern Thailand as part of the Global Energy and Water Cycle Experiment (GEWEX) Asian Monsoon Experiment-Tropics (GAME-T). Investigations of rainfall amounts, intensities, durations, and frequencies in the rainy season revealed strong orographic rainfall enhancement in the region. The larger amount of high-altitude rainfall was attributed to duration and frequency rather than intensity. Despite large rainfall variations, similar patterns were found in the two study years, 1998 and 1999.
Abstract
As a first step toward designing a comprehensive model for validating land surface hydrology and river flow in Earth system models, a global river channel network has been prepared at 1° latitude × 1° longitude resolution. The end product is the Total Runoff Integrating Pathways (TRIP) network. The aim of TRIP is to provide information of lateral water movement over land following the paths of river channels. Flow directions were determined from vector data of river channels and river pathways available in two recent atlases; however, an automatic procedure using a digital elevation map of the corresponding horizontal resolution was used as a first guess. In this way, a template to convert the river discharge data into mean runoff per unit area of the basin has been obtained. One hundred eighty major rivers are identified and adequately resolved; they cover 63% of land, excluding Antarctica and Greenland. Most of the river basin sizes are well within a 20% difference of published values, with a root-mean-square error of approximately 10%. Furthermore, drainage areas for more than 400 gauging stations were delineated. Obviously, the stream lengths in TRIP are shorter than the natural lengths published as data. This is caused by the meandering of rivers in the real world. Meandering ratio (r M ), the ratio of actual (published) river length to the idealized river length, has been calculated. Averaged globally for all available data, r M is 1.4, although it is 1.3 for rivers with areas larger than 500,000 km2. The r M data will be useful in the design of the Scheme for Total Runoff Integrating Pathways (STRIP). In the current form, TRIP can be used as a template for producing a time series of river flow using a simple version of STRIP.
Abstract
As a first step toward designing a comprehensive model for validating land surface hydrology and river flow in Earth system models, a global river channel network has been prepared at 1° latitude × 1° longitude resolution. The end product is the Total Runoff Integrating Pathways (TRIP) network. The aim of TRIP is to provide information of lateral water movement over land following the paths of river channels. Flow directions were determined from vector data of river channels and river pathways available in two recent atlases; however, an automatic procedure using a digital elevation map of the corresponding horizontal resolution was used as a first guess. In this way, a template to convert the river discharge data into mean runoff per unit area of the basin has been obtained. One hundred eighty major rivers are identified and adequately resolved; they cover 63% of land, excluding Antarctica and Greenland. Most of the river basin sizes are well within a 20% difference of published values, with a root-mean-square error of approximately 10%. Furthermore, drainage areas for more than 400 gauging stations were delineated. Obviously, the stream lengths in TRIP are shorter than the natural lengths published as data. This is caused by the meandering of rivers in the real world. Meandering ratio (r M ), the ratio of actual (published) river length to the idealized river length, has been calculated. Averaged globally for all available data, r M is 1.4, although it is 1.3 for rivers with areas larger than 500,000 km2. The r M data will be useful in the design of the Scheme for Total Runoff Integrating Pathways (STRIP). In the current form, TRIP can be used as a template for producing a time series of river flow using a simple version of STRIP.
Abstract
It is now widely recognized that tropical deforestation can change the regional climate significantly. The increasing population and the spreading deforestation in the Indochina Peninsula, especially in Thailand, make it urgent to assess the effects of deforestation on the regional climate. Most of the previous numerical experiments generally have shown that decreases in precipitation occur as a result of deforestation. However, in most cases, these hydrometeorological changes have not been detected in observations. In this study, the nonparametric Mann–Kendall rank test and linear regression analysis were applied to analyze precipitation data obtained over a period of more than 40 yr, for each month, at each meteorological station in Thailand. Significant decreases in precipitation over Thailand were detected only in the time series of monthly precipitation in September. Amounts of precipitation recorded at many meteorological stations in September have decreased by approximately 100 mm month−1 (approximately 30% relative change) over the past three or four decades. Numerical experiments with a regional climate model based on the Regional Atmospheric Modeling System with a simple land surface scheme were carried out for the Indochina Peninsula. In these experiments, the type of vegetation in the northeastern part of Thailand was specified as either short vegetation (the current vegetation type) or forest (the former vegetation type). The experiments were carried out using the initial and boundary meteorological conditions of August and September in 1992–94. The initial and boundary conditions were interpolated from the data of the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis. In these numerical experiments, a decrease in precipitation over the deforested area was obtained for September, but not for August. The magnitude of the mean decrease in precipitation over the whole deforested area in these experiments was 26 mm month−1 (7% relative change), and the local maximum decrease was 88 mm month−1 (29% relative change). Precipitation in the wet season over the Indochina Peninsula basically occurs under the influence of the Southeast Asian summer monsoon system. The strong summer monsoon westerlies bring abundant moisture to the Indochina Peninsula as a source of precipitation. The monsoon westerlies are the predominant external force influencing the regional climate. However, the strong westerlies over the Indochina Peninsula disappear in September, although that is typically the month of maximum precipitation. Accordingly, it is inferred that the effect of local deforestation appears significantly only in September because of the absence of this strong external force.
Abstract
It is now widely recognized that tropical deforestation can change the regional climate significantly. The increasing population and the spreading deforestation in the Indochina Peninsula, especially in Thailand, make it urgent to assess the effects of deforestation on the regional climate. Most of the previous numerical experiments generally have shown that decreases in precipitation occur as a result of deforestation. However, in most cases, these hydrometeorological changes have not been detected in observations. In this study, the nonparametric Mann–Kendall rank test and linear regression analysis were applied to analyze precipitation data obtained over a period of more than 40 yr, for each month, at each meteorological station in Thailand. Significant decreases in precipitation over Thailand were detected only in the time series of monthly precipitation in September. Amounts of precipitation recorded at many meteorological stations in September have decreased by approximately 100 mm month−1 (approximately 30% relative change) over the past three or four decades. Numerical experiments with a regional climate model based on the Regional Atmospheric Modeling System with a simple land surface scheme were carried out for the Indochina Peninsula. In these experiments, the type of vegetation in the northeastern part of Thailand was specified as either short vegetation (the current vegetation type) or forest (the former vegetation type). The experiments were carried out using the initial and boundary meteorological conditions of August and September in 1992–94. The initial and boundary conditions were interpolated from the data of the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis. In these numerical experiments, a decrease in precipitation over the deforested area was obtained for September, but not for August. The magnitude of the mean decrease in precipitation over the whole deforested area in these experiments was 26 mm month−1 (7% relative change), and the local maximum decrease was 88 mm month−1 (29% relative change). Precipitation in the wet season over the Indochina Peninsula basically occurs under the influence of the Southeast Asian summer monsoon system. The strong summer monsoon westerlies bring abundant moisture to the Indochina Peninsula as a source of precipitation. The monsoon westerlies are the predominant external force influencing the regional climate. However, the strong westerlies over the Indochina Peninsula disappear in September, although that is typically the month of maximum precipitation. Accordingly, it is inferred that the effect of local deforestation appears significantly only in September because of the absence of this strong external force.
Abstract
The effects of natural and anthropogenic heterogeneity on a hydrological simulation are evaluated using a distributed biosphere hydrological model (DBHM) system. The DBHM embeds a biosphere model into a distributed hydrological scheme, representing both topography and vegetation in a mesoscale hydrological simulation, and the model system includes an irrigation scheme. The authors investigated the effects of two kinds of variability, precipitation variability and the variability of irrigation redistributing runoff, representing natural and anthropogenic heterogeneity, respectively, on hydrological processes. Runoff was underestimated if rainfall was placed spatially uniformly over large grid cells. Accounting for precipitation heterogeneity improved the runoff simulation. However, the negative runoff contribution, namely, the situation that mean annual precipitation is less than evapotranspiration, cannot be simulated by only considering the natural heterogeneity. This constructive model shortcoming can be eliminated by accounting for anthropogenic heterogeneity caused by irrigation water withdrawals. Irrigation leads to increased evapotranspiration and decreased runoff, and surface soil moisture in irrigated areas increases because of irrigation. Simulations performed for the Yellow River basin of China indicated streamflow decreases of 41% due to irrigation effects. The latent heat flux in the peak irrigation season [June–August (JJA)] increased 3.3 W m−2 with a decrease in the ground surface temperature of 0.1 K for the river basin. The maximum simulated increase in the latent heat flux was 43 W m−2, and the ground temperature decrease was 1.6 K in the peak irrigation season.
Abstract
The effects of natural and anthropogenic heterogeneity on a hydrological simulation are evaluated using a distributed biosphere hydrological model (DBHM) system. The DBHM embeds a biosphere model into a distributed hydrological scheme, representing both topography and vegetation in a mesoscale hydrological simulation, and the model system includes an irrigation scheme. The authors investigated the effects of two kinds of variability, precipitation variability and the variability of irrigation redistributing runoff, representing natural and anthropogenic heterogeneity, respectively, on hydrological processes. Runoff was underestimated if rainfall was placed spatially uniformly over large grid cells. Accounting for precipitation heterogeneity improved the runoff simulation. However, the negative runoff contribution, namely, the situation that mean annual precipitation is less than evapotranspiration, cannot be simulated by only considering the natural heterogeneity. This constructive model shortcoming can be eliminated by accounting for anthropogenic heterogeneity caused by irrigation water withdrawals. Irrigation leads to increased evapotranspiration and decreased runoff, and surface soil moisture in irrigated areas increases because of irrigation. Simulations performed for the Yellow River basin of China indicated streamflow decreases of 41% due to irrigation effects. The latent heat flux in the peak irrigation season [June–August (JJA)] increased 3.3 W m−2 with a decrease in the ground surface temperature of 0.1 K for the river basin. The maximum simulated increase in the latent heat flux was 43 W m−2, and the ground temperature decrease was 1.6 K in the peak irrigation season.
Abstract
This study investigates the projections of river discharge for 24 major rivers in the world during the twenty-first century simulated by 19 coupled atmosphere–ocean general circulation models based on the Special Report on Emissions Scenarios A1B scenario. To reduce model bias and uncertainty, a weighted ensemble mean (WEM) is used for multimodel projections. Although it is difficult to reproduce the present river discharge in any single model, the WEM results produce more accurate reproduction for most rivers, except those affected by anthropogenic water usage. At the end of the twenty-first century, the annual mean precipitation, evaporation, and runoff increase in high latitudes of the Northern Hemisphere, southern to eastern Asia, and central Africa. In contrast, they decrease in the Mediterranean region, southern Africa, southern North America, and Central America. Although the geographical distribution of the changes in precipitation and runoff tends to coincide with that in the river discharge, it should be emphasized that the change in runoff at the upstream region affects the river flow in the downstream region. In high-latitude rivers (Amur, Lena, MacKenzie, Ob, Yenisei, and Yukon), the discharge increases, and the peak timing shifts earlier because of an earlier snowmelt caused by global warming. Discharge tends to decrease for the rivers in Europe to the Mediterranean region (Danube, Euphrates, and Rhine), and southern United Sates (Rio Grande).
Abstract
This study investigates the projections of river discharge for 24 major rivers in the world during the twenty-first century simulated by 19 coupled atmosphere–ocean general circulation models based on the Special Report on Emissions Scenarios A1B scenario. To reduce model bias and uncertainty, a weighted ensemble mean (WEM) is used for multimodel projections. Although it is difficult to reproduce the present river discharge in any single model, the WEM results produce more accurate reproduction for most rivers, except those affected by anthropogenic water usage. At the end of the twenty-first century, the annual mean precipitation, evaporation, and runoff increase in high latitudes of the Northern Hemisphere, southern to eastern Asia, and central Africa. In contrast, they decrease in the Mediterranean region, southern Africa, southern North America, and Central America. Although the geographical distribution of the changes in precipitation and runoff tends to coincide with that in the river discharge, it should be emphasized that the change in runoff at the upstream region affects the river flow in the downstream region. In high-latitude rivers (Amur, Lena, MacKenzie, Ob, Yenisei, and Yukon), the discharge increases, and the peak timing shifts earlier because of an earlier snowmelt caused by global warming. Discharge tends to decrease for the rivers in Europe to the Mediterranean region (Danube, Euphrates, and Rhine), and southern United Sates (Rio Grande).
Abstract
A simple algorithm is presented for transferring root-zone soil moisture from surface soil moisture data on a global scale. Analysis of offline soil moisture data shows that the climatological relationship between surface and root-zone soil moisture becomes linear when appropriate time lags are applied. The climatological relationship of root-zone soil moisture among different land surface models (LSMs) is also linear; therefore, the root-zone and surface soil moisture obtained from one LSM can be applied to another. The algorithm is then applied to the surface soil moisture observations made by the precipitation radar on board the Tropical Rainfall Measuring Mission precipitation radar (TRMM/PR), and the transferred root-zone soil moisture is input to a general circulation model (GCM) summer—June, July, August—precipitation simulation as the boundary condition. The approach is computationally efficient, and the simulation using the root-zone soil moisture by the transfer method is much better than a simulation using root-zone soil moisture without the transfer method, assuming that the volumetric percentage of TRMM/PR is representative of the root zone. The result indicates that the simple transfer process will increase the utility of surface soil moisture data for a GCM.
Abstract
A simple algorithm is presented for transferring root-zone soil moisture from surface soil moisture data on a global scale. Analysis of offline soil moisture data shows that the climatological relationship between surface and root-zone soil moisture becomes linear when appropriate time lags are applied. The climatological relationship of root-zone soil moisture among different land surface models (LSMs) is also linear; therefore, the root-zone and surface soil moisture obtained from one LSM can be applied to another. The algorithm is then applied to the surface soil moisture observations made by the precipitation radar on board the Tropical Rainfall Measuring Mission precipitation radar (TRMM/PR), and the transferred root-zone soil moisture is input to a general circulation model (GCM) summer—June, July, August—precipitation simulation as the boundary condition. The approach is computationally efficient, and the simulation using the root-zone soil moisture by the transfer method is much better than a simulation using root-zone soil moisture without the transfer method, assuming that the volumetric percentage of TRMM/PR is representative of the root zone. The result indicates that the simple transfer process will increase the utility of surface soil moisture data for a GCM.
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.
