Bayesian Multi-Scale Spatio-Temporal Modeling of Precipitation in the Indus Watershed

Christensen, Michael F.; Heaton, Matthew J.; Rupper, S.; Reese, C. Shane; Christensen, William F.

doi:10.3389/feart.2019.00210

Cited by 7 publications

(7 citation statements)

References 33 publications

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“…Until such improved near real-time precipitation products are made available, precipitation climatologies, such as the GPCC Climatology, could at least be used to correct the mean bias in precipitation for areas such as the Indus basin. Another recent study of precipitation products [13] also showed that MERRA-2 tended to have lower precipitation around the Indus watershed than APHRODITE and TMPA, while ERA-5 had higher precipitation, although that study did not evaluate how these products compared to station observations. GPCC, supported by CRU, showed a significant increase in precipitation over the Indus basin since the end of the 19th Century.…”

Section: Discussionmentioning

confidence: 93%

“…Moreover, there is high uncertainty owing to divergent behavior of climate models and limited ground observations [9][10][11]. Sparsity and discontinuity of climate and hydrologic observations make it difficult to evaluate the accuracy of hydrologic and climate models and create gaps in the scientific understanding needed to provide evidence for policy decisions [12,13]. Globally, there is recognition of an increased need for employing statistical analyses to provide better information about long-term changes and variability of precipitation as a result of the changing climate and consequent greater exposure to risks such as droughts and floods [14].…”

Section: Introductionmentioning

confidence: 99%

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Precipitation Trends over the Indus Basin

Krakauer

Lakhankar

Dars

2019

Climate

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A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in such cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management.

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Section: Discussionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Precipitation Trends over the Indus Basin

Krakauer

Lakhankar

Dars

2019

Climate

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show abstract

“…Hence, the climatologies for precipitation amount, number of days with precipitation over a given threshold and cloudiness of the different experiments were intercompared for the BASE, ARI and ARCI simulations. The ERA5 (Hrarsbach and Dee, 2016) reanalysis data were used to calculate the added value of the aerosol experiments, since they have already been validated for precipitation (Albergel et al, 2018;Christensen et al, 2019;Hwang et al, 2019). Also represented are the comparison of the annual and seasonal climatologies for other atmospheric fields such as sea level pressure (slp), geopotential height (Z) and temperature (T ) at 1000, 750 and 500 mb, maximum and minimum temperatures (tasmax, tasmin), daily temperature range (dtr), and solar radiation at surface (rsds) as well as mean temporal fields of the particulate matter (PM 10 , PM 2.5 ), BC (black carbon) and AOD.…”

Section: Methodsmentioning

confidence: 99%

Precipitation response to aerosol–radiation and aerosol–cloud interactions in regional climate simulations over Europe

López-Romero¹,

Montávez

Jerez

et al. 2021

Atmos. Chem. Phys.

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Abstract. The effect of aerosols on regional climate simulations presents large uncertainties due to their complex and non-linear interactions with a wide variety of factors, including aerosol–radiation (ARI) and aerosol–cloud (ACI) interactions. These interactions are strongly conditioned by the meteorological situation and type of aerosol, but, despite their increase, only a limited number of studies have covered this topic from a regional and climatic perspective. This contribution thus aims to quantify the impacts on precipitation of the inclusion of ARI and ACI processes in regional climate simulations driven by ERA20C reanalysis. A series of regional climatic simulations (for the period 1991–2010) for the Euro-CORDEX domain were conducted including ARI and ARI + ACI (ARCI), establishing as a reference a simulation where aerosols were not included interactively (BASE). The results show that the effects of ARI and ACI on time-mean spatially averaged precipitation over the whole domain are limited. However, a spatial redistribution of precipitation occurs when the ARI and ACI processes are introduced into the model, as well do changes in the precipitation intensity regimes. The main differences with respect to the base-case simulations occur in central Europe, where a decrease in precipitation is associated with a depletion in the number of rainy days and clouds at low level (CLL). This reduction in precipitation presents a strong correlation with the ratio PM2.5∕PM10, since the decrease is especially intense during those events with high values of that ratio (pointing to high levels of anthropogenic aerosols) over central Europe. The precipitation decrease occurs for all ranges of precipitation rates. On the other hand, the model produces an increase in precipitation over the eastern Mediterranean basin associated with an increase in clouds and rainy days when ACIs are implemented. Here, the change is caused by the high presence of PM10 (low PM2.5∕PM10 ratios, pointing to natural aerosols). In this case, the higher amount of precipitation affects only days with low rates of precipitation. Finally, there are some disperse areas where the inclusion of aerosols leads to an increase in precipitation, especially for moderate and high precipitation rates.

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“…Hence, the climatologies for precipitation amount, number of days with precipitation over a given threshold and cloudiness of the different experiments have been intercompared for BASE, ARI and ACI simulations. The data used to evaluate the added value of the aerosol experiments was the ERA5 (Hrarsbach and Dee, 2016) reanalysis, since it has already been validated for precipitation (Albergel et al, 2018;Christensen et al, 2019;Hwang et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

Precipitation response to Aerosol-Radiation and Aerosol-Cloud Interactions in Regional Climate Simulations over Europe

López-Romero¹,

Montávez²,

Jerez³

et al. 2020

Preprint

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Abstract. The effect of aerosols on regional climate simulations presents large uncertainties due to their complex and non-linear interactions with a wide variety of factors, including aerosol-radiation (ARI) and aerosol-cloud (ACI) interactions. These interactions are strongly conditioned by the meteorological situation and the type of aerosol. Despite increasing, there is nowadays a very limited number of studies covering this topic from a regional and climatic perspective. Hence, this contribution aims at quantifying the impacts on precipitation of the inclusion of ARI and ACI processes in regional climate simulations driven by ERA20C reanalysis. A series of regional climatic simulations (years 1991–2010) for the Euro-CORDEX domain have been conducted including ARI and ACI, establishing as reference a simulations where aerosols have not been included interactively (BASE). The results show that the effects of ARI and ACI on mean spatially averaged precipitation are limited. However, a spatial redistribution of precipitation occurs when introducing the ARI and ACI processes in the model; as well as some changes in the intensity precipitation regimes. The main differences with respect to the base-case simulations occur in central Europe, where a decrease in precipitation is associated with a depletion in the number of rainy days and low clouds. This reduction in precipitation presents a strong correlation with the ratio PM2.5/PM10, since the decrease is specially intense during those events with high values of that ratio (pointing to high levels of anthropogenic aerosols) over the aforementioned area. The precipitation decrease occurs for all ranges of precipitation rates. On the other hand, the model produces an increase in precipitation over the western Mediterranean basin associated with an increase of clouds and rainy days when ACI are implemented. Here the change is caused by the high presence of PM10 (low PM2.5/PM10 ratios, pointing to natural aerosols). In this case, the higher amount of precipitation affects only to those days with low rates of precipitation. Finally, there are some disperse areas were the inclusion of aerosols leads to an increase in precipitation, specially for moderate and high precipitation rates.

show abstract

Bayesian Multi-Scale Spatio-Temporal Modeling of Precipitation in the Indus Watershed

Cited by 7 publications

References 33 publications

Precipitation Trends over the Indus Basin

Precipitation Trends over the Indus Basin

Precipitation response to aerosol–radiation and aerosol–cloud interactions in regional climate simulations over Europe

Precipitation response to Aerosol-Radiation and Aerosol-Cloud Interactions in Regional Climate Simulations over Europe

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