scholarly journals Precipitation downscaling using a probability-matching approach and geostationary infrared data: An evaluation over six climate regions

2017 ◽  
Author(s):  
Ruifang Guo ◽  
Yuanbo Liu ◽  
Han Zhou ◽  
Yaqiao Zhu
Keyword(s):  
Water Cycle ◽  
Rain Gauge ◽  
Cumulative Distribution ◽  
Rainfall Regime ◽  
Precipitation Data ◽  
Main Hypothesis ◽  
Global Water Cycle ◽  
Basin Scale ◽  
Daily Scale ◽  
Spatio Temporal

Abstract. Precipitation is one of the most important components of the global water cycle. Precipitation data at high spatial and temporal resolutions are crucial for basin-scale hydrological and meteorological studies. In this study, we proposed a cumulative distribution of frequency (CDF)-based downscaling method (DCDF) to obtain hourly 0.05° × 0.05° precipitation data. The main hypothesis is that a variable with the same resolution of target data should produce a CDF that is similar to the reference data. The method was demonstrated using the 3 hourly 0.25° × 0.25° Climate Prediction Center Morphing method (CMORPH) dataset and the hourly 0.05° × 0.05° FY2-E Geostationary (GEO) Infrared (IR) temperature brightness (Tb) data. Initially, power function relationships were established between precipitation rate and Tb for each 1° × 1° region. Then the CMORPH data were downscaled to 0.05° × 0.05°. The downscaled results were validated over diverse rainfall regimes in China. Within each rainfall regime, the fitting functions coefficients were able to implicitly reflect the characteristics of precipitation. Qualitatively, the downscaled estimates were able to capture more details about rainfall motions and changes. Quantitatively, the time series of the downscaled estimates were more similar to the rain gauge data than the original CMORPH product at the daily scale. The downscaled estimates not only improved spatio-temporal resolutions, but also performed better (Bias: −7.35 %~10.35 %; correlation coefficient (CC): 0.48~0.60) than the CMORPH product (Bias: 20.82 %~94.19 %; CC: 0.31~0.59) over convective precipitating regions. The downscaled results performed as well as the CMORPH product over regions dominated with frontal rain systems and performed relatively poorly over mountainous or hilly areas where orographic rain systems dominate.

scholarly journals Precipitation downscaling using a probability-matching approach and geostationary infrared data: an evaluation over six climate regions

2018 ◽  
Vol 22 (7) ◽  
pp. 3685-3699 ◽  
Author(s):  
Ruifang Guo ◽  
Yuanbo Liu ◽  
Han Zhou ◽  
Yaqiao Zhu
Keyword(s):  
Water Cycle ◽  
Regional Scale ◽  
Rain Gauge ◽  
Cumulative Distribution ◽  
Rainfall Regime ◽  
Precipitation Data ◽  
Main Hypothesis ◽  
Basin Scale ◽  
Spatio Temporal ◽  
Better Than

Abstract. Precipitation is one of the most important components of the global water cycle. Precipitation data at high spatial and temporal resolutions are crucial for basin-scale hydrological and meteorological studies. In this study, we propose a cumulative distribution of frequency (CDF)-based downscaling method (DCDF) to obtain hourly 0.05∘ × 0.05∘ precipitation data. The main hypothesis is that a variable with the same resolution of target data should produce a CDF that is similar to the reference data. The method was demonstrated using the 3-hourly 0.25∘ × 0.25∘ Climate Prediction Center morphing method (CMORPH) dataset and the hourly 0.05∘ × 0.05∘ FY2-E geostationary (GEO) infrared (IR) temperature brightness (Tb) data. Initially, power function relationships were established between the precipitation rate and Tb for each 1∘ × 1∘ region. Then the CMORPH data were downscaled to 0.05∘ × 0.05∘. The downscaled results were validated over diverse rainfall regimes in China. Within each rainfall regime, the fitting functions' coefficients were able to implicitly reflect the characteristics of precipitation. Quantitatively, the downscaled estimates not only improved spatio-temporal resolutions, but also performed better (bias: −7.35–10.35 %; correlation coefficient, CC: 0.48–0.60) than the CMORPH product (bias: 20.82–94.19 %; CC: 0.31–0.59) over convective precipitating regions. The downscaled results performed as well as the CMORPH product over regions dominated with frontal rain systems and performed relatively poorly over mountainous or hilly areas where orographic rain systems dominate. Qualitatively, at the daily scale, DCDF and CMORPH had nearly equivalent performances at the regional scale, and 79 % DCDF may perform better than or nearly equivalently to CMORPH at the point (rain gauge) scale. The downscaled estimates were able to capture more details about rainfall motion and changes under the condition that DCDF performs better than or nearly equivalently to CMORPH.

GRACE/GRACE-FO to constrain regional to global Evapotranspiration

2020 ◽  
Author(s):  
John Reager ◽  
Madeleine Pascolini-Campbell
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Water Flux ◽  
Mass Conservation ◽  
Mass Change ◽  
Global Water Cycle ◽  
Basin Scale ◽  
Global Land ◽  
Terrestrial Water ◽  
Global Water

<p>A frontier in hydrology lies in understanding the potential impacts of a warming planet on water cycle variability from regional to global scales.  The fluxes that constitute the terrestrial water cycle present various complexity in observability, with Evapotranspiration (ET) being generally the most challenging variable to quantify directly.  Because of the ability to apply mass conservation and to "close" a water flux budget across scales, mass change measurements present the best opportunity to quantify evapotranspiration and changes in evapotranspiration at larger scales, ranging from basins to global. Here we present work on: (1) using GRACE/GFO observations to estimate basin-scale ET in the continental United States as a target for validation and error analysis of up-scaled ET products from other sources, and (2) using GRACE/GFO observations to estimate ET globally over the full joint record (2003-2020) in order to quantify observed changes in the global water cycle.  We find that because of the way that errors in mass change measurements inherently change in scale (i.e. decreasing with larger study domains), GRACE/GFO measurements offer a very clear and robust uncertainty quantification approach for large scale ET monitoring.  We also find that there is a clear and statistically significant signal in global land ET over the record length that indicates changes in the global water cycle consistent with our understanding of climate change.  These methods and results will be presented and discussed.</p>

scholarly journals From regional climate simulations to the hydrological information needed for basin scale impact studies

2010 ◽  
Vol 26 ◽  
pp. 25-31
Author(s):  
I. Portoghese ◽  
E. Bruno ◽  
M. Vurro
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Climate Change Impacts ◽  
Stochastic Modelling ◽  
Rain Gauge ◽  
Hydrological Processes ◽  
Rainfall Regime ◽  
Basin Scale

Abstract. The accuracy of local downscaling of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes because the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows, and groundwater recharge. In this study, the output of a regional climate model (RCM) is downscaled using a stochastic modelling of the point rainfall process able to adequately reproduce the daily rainfall intermittency which is one of the crucial aspects for the hydrological processes characterizing Mediterranean environments. The historical time-series from a dense rain-gauge network were used for the analysis of the RCM bias in terms of dry and wet daily period and then to investigate the predicted alteration in the local rainfall regime. A Poisson Rectangular Pulse (PRP) model (Rodriguez-Iturbe et al., 1987) was finally adopted for the stochastic generation of local daily rainfall as a continuous-time point process with forcing parameters resulting from the bias correction of the RCM scenario.

scholarly journals Drought Hazard Mapping from Regional Climate Multimodel Ensemble over Spain

2015 ◽  
Vol 10 (2) ◽  
pp. 17
Author(s):  
Sandra G. Garcia Galiano ◽  
Juan Diego Giraldo Osorio ◽  
Patricia Olmos Gimenez
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Regional Climate ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Hazard Mapping ◽  
Annual Maximum ◽  
Dry Spells ◽  
Basin Scale ◽  
Spatio Temporal

<p>Improving the knowledge about the impacts of climate change on extreme drought events at basin scale, is important for decision makers in order to develop drought contingency plans which are the leading edge of adaptive management strategy. Considering high-resolution grids of observed daily rainfall and information provided by latest-generation Regional Climate Models (RCMs), the changes in the spatio-temporal patterns of extreme droughts in peninsular Spain are assessed. The non-stationarity character of time series, due to climate and anthropogenic changes, is represented by probabilistic models considering the time evolution of probability density function (PDF) parameters fitted to annual maximum lengths of dry spells time series. By a PDF ensemble from 17 RCMs, the spatio-temporal variability exhibited by the RCMs is represented. Scoring of models is based in the goodness-of-fit to CDFs (cumulative distribution functions) of observed annual maximum dry spells lengths. The reliability and skills of RCMs are assessed, for building the PDF ensemble, at grid site for the study area. Therefore, by adjusting PDF to series of annual maximum dry spells lengths, applying GAMLSS and bootstrapping techniques, the assessment of regional changes and trends associated to high returns periods (<em>Tr</em> = 25 and 50 yr.) is assessed. In general, an intensification of drought events for 2050 horizon, in contrast with 1990, is expected. By increasing return periods, the length of the annual maximum dry spells rises, albeit with a smaller number of areas with significant differences. The areas prone to extreme droughts in mainland Spain are identified.</p>

Evaluation of the TRMM Product for Spatio-temporal Characteristics of Precipitation over Nepal (1998-2018)

2020 ◽  
Vol 25 (2) ◽  
pp. 39-48
Author(s):  
Kalpana Hamal ◽  
Nitesh Khadka ◽  
Samresh Rai ◽  
Bharat Badayar Joshi ◽  
Jagdish Dotel ◽  
...  
Keyword(s):  
Water Cycle ◽  
Winter Season ◽  
Temporal Distribution ◽  
Tropical Rainfall Measuring Mission ◽  
Good Alternative ◽  
High Elevation ◽  
Large Error ◽  
Rain Gauge ◽  
Mean Annual Precipitation ◽  
Spatio Temporal

Precipitation is a fundamental component of the water cycle and integral to the society and the ecosystem. Further, continuous monitoring of precipitation is essential for predicting severe weather, monitoring droughts, and high-intensity related extremes. The present study evaluated the spatio-temporal distribution of precipitation and trends between 1998– 2018 using Tropical Rainfall Measuring Mission (TRMM) (3B43-V7) with reference to 142-gauge observations over Nepal. TRMM moderately captured precipitation patterns' overall characteristics, although underestimated the mean annual precipitation during the study period. TRMM precipitation product well captured the seasonal variation of the observed precipitation with the highest correlation in the winter season. The decreasing seasonal and annual trend was found in both observed and TRMM products, with the highest (lowest) decreasing trend observed during the monsoon (winter) season. It was also noted that the TRMM product showed a smaller bias before 2007, while a large error was found after 2007, especially in the monsoon months. In general, the TRMM product is a good alternative to observe rain gauge measurement in Nepal. However, there is still space for further improvement in rainfall retrieval algorithms, especially in high-elevation areas during the winter season.

scholarly journals Climate-dependent propagation of precipitation uncertainty into the water cycle

2020 ◽  
Vol 24 (7) ◽  
pp. 3725-3735
Author(s):  
Ali Fallah ◽  
Sungmin O ◽  
Rene Orth
Keyword(s):  
Hydrological Modeling ◽  
Water Cycle ◽  
Rain Gauge ◽  
Data Sets ◽  
Precipitation Data ◽  
Multiple Sources ◽  
Study Region ◽  
Global Precipitation Climatology Centre ◽  
Wide Range ◽  
The Impact

Abstract. Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over poorly gauged regions. This study examines the usefulness of current state-of-the-art precipitation data sets in hydrological modeling. For this purpose, we force a conceptual hydrological model with multiple precipitation data sets in >200 European catchments to obtain runoff and evapotranspiration. We consider a wide range of precipitation products, which are generated via (1) the interpolation of gauge measurements (E-OBS and Global Precipitation Climatology Centre (GPCC) V.2018), (2)  data assimilation into reanalysis models (ERA-Interim, ERA5, and Climate Forecast System Reanalysis – CFSR), and (3) a combination of multiple sources (Multi-Source Weighted-Ensemble Precipitation; MSWEP V2). Evaluation is done at the daily and monthly timescales during the period of 1984–2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs; in contrast, simulated evapotranspiration is generally much less influenced in our comparatively wet study region. We also find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation data sets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the particularly strong agreement, while ERA5, GPCC V.2018, and MSWEP V2 show good performances. We further reveal climate-dependent performance variations of the considered data sets, which can be used to guide their future development. The overall best agreement is achieved when using an ensemble mean generated from all the individual products. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions, such as central Europe, there are increasing implications for evapotranspiration in drier regions.

The global water cycle and continental erosion during Phanerozoic time (570 my)

1989 ◽  
Vol 289 (4) ◽  
pp. 455-483 ◽  
Author(s):  
Y. Tardy ◽  
R. N'Kounkou ◽  
J.-L. Probst
Keyword(s):  
Water Cycle ◽  
Global Water Cycle ◽  
Continental Erosion ◽  
Global Water

scholarly journals Evaluation of IMERG Level-3 Products in Depicting the July to October Rainfall over Taiwan: Typhoon Versus Non-Typhoon

2021 ◽  
Vol 13 (4) ◽  
pp. 622
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Ya-Hui Chang ◽  
Cheng-An Lee
Keyword(s):  
Real Time ◽  
Tropical Rainfall Measuring Mission ◽  
Temporal Variations ◽  
Rain Gauge ◽  
Advantages And Disadvantages ◽  
Level 3 ◽  
Spatio Temporal ◽  
Typhoon Season ◽  
Early Late ◽  
Better Than

This study assesses the performance of satellite precipitation products (SPPs) from the latest version, V06B, Integrated Multi-satellitE Retrievals for Global Precipitation Mission (IMERG) Level-3 (including early, late, and final runs), in depicting the characteristics of typhoon season (July to October) rainfall over Taiwan within the period of 2000–2018. The early and late runs are near-real-time SPPs, while final run is post-real-time SPP adjusted by monthly rain gauge data. The latency of early, late, and final runs is approximately 4 h, 14 h, and 3.5 months, respectively, after the observation. Analyses focus on the seasonal mean, daily variation, and interannual variation of typhoon-related (TC) and non-typhoon-related (non-TC) rainfall. Using local rain-gauge observations as a reference for evaluation, our results show that all IMERG products capture the spatio-temporal variations of TC rainfall better than those of non-TC rainfall. Among SPPs, the final run performs better than the late run, which is slightly better than the early run for most of the features assessed for both TC and non-TC rainfall. Despite these differences, all IMERG products outperform the frequently used Tropical Rainfall Measuring Mission 3B42 v7 (TRMM7) for the illustration of the spatio-temporal characteristics of TC rainfall in Taiwan. In contrast, for the non-TC rainfall, the final run performs notably better relative to TRMM7, while the early and late runs showed only slight improvement. These findings highlight the advantages and disadvantages of using IMERG products for studying or monitoring typhoon season rainfall in Taiwan.

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