scholarly journals Variations of future precipitations in Poyang Lake Watershed under the global warming using a spatiotemporally distributed downscaling model

2018 ◽  
Author(s):  
Ling Zhang ◽  
Xiaoling Chen ◽  
Jianzhong Lu ◽  
Dong Liang
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Poyang Lake ◽  
Dry Season ◽  
Global Climate Models ◽  
Wet Season ◽  
Temporal And Spatial Distribution ◽  
Precipitation Frequency ◽  
Change Rate ◽  
Precipitation Changes

Abstract. Traditional statistic downscaling methods are processed on independent stations, which ignores spatial correlations and spatiotemporal heterogeneity. In this study, a spatiotemporally distributed downscaling model (STDDM) was developed. The method interpolated observations and GCMs (Global Climate Models) simulations to continual finer grids; then created relationship, respectively for each grid at each time. We applied the STDDM in precipitation downscaling of Poyang Lake Watershed using MRI-CGCM3 (Meteorological Research Institute Coupled Ocean-Atmosphere General Circulation Model3), with an acceptant uncertainty of ≤ 4.9 %, and created future precipitation changes from 1998 to 2100 (1998–2012 in the historical and 2013–2100 in RCP8.5 scenario). The precipitation changes showed increasing heterogeneities in temporal and spatial distribution under the future climate warming. In the temporal pattern, the wet season precipitation increased with change rate (CR) = 7.33 mm/10a (11.66 mm/K) while the dry season precipitations decreased with CR = −0.92 mm/10a (−4.31 mm/K). The extreme precipitation frequency and intensity were enhanced with CR = 0.49 days/10a and 7.2 mm•day-1/10a respectively. In the spatial pattern, precipitations in wet or dry season showed an uneven change rate over the watershed, and the wet or dry area exhibited a wetter or drier condition in the wet or dry season. Analysis with temperature increases showed precipitation changes appeared significantly (p 

scholarly journals Precipitation projections using a spatiotemporally distributed method: a case study in the Poyang Lake watershed based on the MRI-CGCM3

2019 ◽  
Vol 23 (3) ◽  
pp. 1649-1666 ◽  
Author(s):  
Ling Zhang ◽  
Xiaoling Chen ◽  
Jianzhong Lu ◽  
Xiaokang Fu ◽  
Yufang Zhang ◽  
...  
Keyword(s):  
Climate Warming ◽  
General Circulation ◽  
Poyang Lake ◽  
Global Climate Model ◽  
Regional Scale ◽  
Resource Planning ◽  
Dry Season ◽  
Wet Season ◽  
Basin Scale ◽  
Precipitation Changes

Abstract. To bridge the gap between large-scale GCM (global climate model) outputs and regional-scale climate requirements of hydrological models, a spatiotemporally distributed downscaling model (STDDM) was developed. The STDDM was done in three stages: (1) up-sampling grid-observations and GCM simulations for spatially continuous finer grids, (2) creating the mapping relationship between the observations and the simulations differently in space and time, and (3) correcting the simulation and producing downscaled data to a spatially continuous grid scale. We applied the STDDM to precipitation downscaling in the Poyang Lake watershed using the MRI-CGCM3 (Meteorological Research Institute Coupled Ocean–Atmosphere General Circulation Model 3), with an acceptable uncertainty of ≤ 4.9 %. Then we created future precipitation changes from 1998 to 2100 (1998–2012 in the historical scenario and 2013–2100 in the RCP8.5 scenario). The precipitation changes increased heterogeneities in temporal and spatial distribution under future climate warming. In terms of temporal patterns, the wet season become wetter, while the dry season become drier. The frequency of extreme precipitation increased, while that of the moderate precipitation decreased. Total precipitation increased, while rainy days decreased. The maximum continuous dry days and the maximum daily precipitation both increased. In terms of spatial patterns, the dry area exhibited a drier condition during the dry season, and the wet area exhibited a wetter condition during the wet season. Analysis with temperature increment showed precipitation changes can be significantly explained by climate warming, with p<0.05 and R≥0.56. The precipitation changes indicated that the downscaling method is reasonable, and the STDDM could be successfully applied to the basin-scale region based on a GCM. The results implied an increasing risk of floods and droughts under global warming, which were a reference for water balance analysis and water resource planning.

scholarly journals California Wintertime Precipitation Bias in Regional and Global Climate Models

2010 ◽  
Vol 49 (10) ◽  
pp. 2147-2158 ◽  
Author(s):  
Peter Caldwell
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Model Resolution ◽  
Grid Spacing ◽  
Precipitation Frequency

Abstract In this paper, wintertime precipitation from a variety of observational datasets, regional climate models (RCMs), and general circulation models (GCMs) is averaged over the state of California and compared. Several averaging methodologies are considered and all are found to give similar values when the model grid spacing is less than 3°. This suggests that California is a reasonable size for regional intercomparisons using modern GCMs. Results show that reanalysis-forced RCMs tend to significantly overpredict California precipitation. This appears to be due mainly to the overprediction of extreme events; RCM precipitation frequency is generally underpredicted. Overprediction is also reflected in wintertime precipitation variability, which tends to be too high for RCMs on both daily and interannual scales. Wintertime precipitation in most (but not all) GCMs is underestimated. This is in contrast to previous studies based on global blended gauge–satellite observations, which are shown here to underestimate precipitation relative to higher-resolution gauge-only datasets. Several GCMs provide reasonable daily precipitation distributions, a trait that does not seem to be tied to model resolution. The GCM daily and interannual variabilities are generally underpredicted.

Agronomic benefits and risks associated with the irrigated peanut–maize production system under a changing climate in northern Australia

2015 ◽  
Vol 66 (11) ◽  
pp. 1167 ◽  
Author(s):  
Yashvir S. Chauhan ◽  
Peter Thorburn ◽  
Jody S. Biggs ◽  
Graeme C. Wright
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Ghg Emissions ◽  
Dry Season ◽  
Global Climate Models ◽  
Irrigation Requirement ◽  
Wet Season ◽  
N Losses ◽  
Maize Production ◽  
Increased Temperature

With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.

scholarly journals What Controls Evapotranspiration in the Amazon Basin?

2007 ◽  
Vol 8 (3) ◽  
pp. 380-395 ◽  
Author(s):  
Natalia Hasler ◽  
Roni Avissar
Keyword(s):  
Water Stress ◽  
Large Scale ◽  
Amazon Basin ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Dry Season ◽  
Global Climate Models ◽  
Net Radiation ◽  
Wet Season

Abstract Global climate models (GCMs) and regional climate models (RCMs) generally show a decrease in the dry season evapotranspiration (ET) rate over the entire Amazon basin. Based on anecdotal observations, it has been suggested that they probably overestimate tropical rain forest water stress. In this study, eddy covariance flux measurements from eight different towers of the Large-Scale Biosphere–Atmosphere Experiment in Amazonia (LBA) were used to provide a first look at the spatial variability and temporal cycle of ET throughout the basin. Results show strong seasonality in ET for stations near the equator (2°–3°S), with ET increasing during the dry season (June–September) and decreasing during the wet season (December–March), both correlated (0.75 to 0.94) and in phase with the net radiation annual cycle. In stations located farther south (9°–11°S) no clear seasonality could be identified in either net radiation or ET. For these more southerly stations, net radiation and ET are still correlated (0.76–0.92) in the wet season, but correlations decrease in the dry season (0–0.71), which is likely associated with water stress. For both pasture sites, located in southern Amazonia, ET decreases during the second half of the dry season, indicating progressively increased water stress. GCMs and RCMs indeed tend to overestimate dry season water stress in the Amazon basin and, therefore, should be revised to better simulate this region, which has a key role in the global hydrometeorology.

scholarly journals A Mechanistically Credible, Poleward Shift in Warm-Season Precipitation Projected for the U.S. Southern Great Plains?

2017 ◽  
Vol 30 (20) ◽  
pp. 8275-8298 ◽  
Author(s):  
Melissa S. Bukovsky ◽  
Rachel R. McCrary ◽  
Anji Seth ◽  
Linda O. Mearns
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Dry Season ◽  
Wet Season ◽  
Southern Great Plains ◽  
Poleward Shift

Abstract Global and regional climate model ensembles project that the annual cycle of rainfall over the southern Great Plains (SGP) will amplify by midcentury. Models indicate that warm-season precipitation will increase during the early spring wet season but shift north earlier in the season, intensifying late summer drying. Regional climate models (RCMs) project larger precipitation changes than their global climate model (GCM) counterparts. This is particularly true during the dry season. The credibility of the RCM projections is established by exploring the larger-scale dynamical and local land–atmosphere feedback processes that drive future changes in the simulations, that is, the responsible mechanisms or processes. In this case, it is found that out of 12 RCM simulations produced for the North American Regional Climate Change Assessment Program (NARCCAP), the majority are mechanistically credible and consistent in the mean changes they are producing in the SGP. Both larger-scale dynamical processes and local land–atmosphere feedbacks drive an earlier end to the spring wet period and deepening of the summer dry season in the SGP. The midlatitude upper-level jet shifts northward, the monsoon anticyclone expands, and the Great Plains low-level jet increases in strength, all supporting a poleward shift in precipitation in the future. This dynamically forced shift causes land–atmosphere coupling to strengthen earlier in the summer, which in turn leads to earlier evaporation of soil moisture in the summer, resulting in extreme drying later in the summer.

scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Middle Miocene ◽  
Climate Models ◽  
Global Climate ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Ice Volume ◽  
Climate Transition

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

scholarly journals Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1032 ◽  
Author(s):  
Ariel Wang ◽  
Francina Dominguez ◽  
Arthur Schmidt
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Precipitation Frequency ◽  
Spatio Temporal ◽  
Climate Change Assessment

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.

Northern Hemisphere Atmospheric Blocking Representation in Global Climate Models: Twenty Years of Improvements?

2016 ◽  
Vol 29 (24) ◽  
pp. 8823-8840 ◽  
Author(s):  
Paolo Davini ◽  
Fabio D’Andrea
Keyword(s):  
Northern Hemisphere ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Global Climate Models ◽  
Main Concern ◽  
Atmospheric Blocking ◽  
Atlantic Sector

Abstract The correct simulation of midlatitude atmospheric blocking has always been a main concern since the earliest days of numerical modeling of Earth’s atmosphere. To this day blocking represents a considerable source of error for general circulation models from both a numerical weather prediction and a climate perspective. In the present work, 20 years of global climate model (GCM) developments are analyzed from the special point of view of Northern Hemisphere atmospheric blocking simulation. Making use of a series of equivalent metrics, three generations of GCMs are compared. This encompasses a total of 95 climate models, many of which are different—successive—versions of the same model. Results from model intercomparison projects AMIP1 (1992), CMIP3 (2007), and CMIP5 (2012) are taken into consideration. Although large improvements are seen over the Pacific Ocean, only minor advancements have been achieved over the Euro-Atlantic sector. Some of the most recent GCMs still exhibit the same negative bias as 20 years ago in this region, associated with large geopotential height systematic errors. Some individual models, nevertheless, have improved and do show good performances in both sectors. Negligible differences emerge among ocean-coupled or atmosphere-only simulations, suggesting weak relevance of sea surface temperature biases. Conversely, increased horizontal resolution seems to be able to alleviate the Euro-Atlantic blocking bias.

scholarly journals A Comparative Frequency Analysis of Maximum Daily Rainfall for a SE Asian Region under Current and Future Climate Conditions

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Velautham Daksiya ◽  
Pradeep Mandapaka ◽  
Edmond Y. M. Lo
Keyword(s):  
General Circulation ◽  
Daily Rainfall ◽  
Circulation Model ◽  
Dry Season ◽  
Wet Season ◽  
Climate Conditions ◽  
Rainfall Extremes ◽  
Annual Maximum Daily Rainfall ◽  
The Impact ◽  
Maximum Daily Rainfall

The impact of changing climate on the frequency of daily rainfall extremes in Jakarta, Indonesia, is analysed and quantified. The study used three different models to assess the changes in rainfall characteristics. The first method involves the use of the weather generator LARS-WG to quantify changes between historical and future daily rainfall maxima. The second approach consists of statistically downscaling general circulation model (GCM) output based on historical empirical relationships between GCM output and station rainfall. Lastly, the study employed recent statistically downscaled global gridded rainfall projections to characterize climate change impact rainfall structure. Both annual and seasonal rainfall extremes are studied. The results show significant changes in annual maximum daily rainfall, with an average increase as high as 20% in the 100-year return period daily rainfall. The uncertainty arising from the use of different GCMs was found to be much larger than the uncertainty from the emission scenarios. Furthermore, the annual and wet seasonal analyses exhibit similar behaviors with increased future rainfall, but the dry season is not consistent across the models. The GCM uncertainty is larger in the dry season compared to annual and wet season.

scholarly journals Improved simulation of clouds over the Southern Ocean in a General Circulation Model

2019 ◽  
Author(s):  
Vidya Varma ◽  
Olaf Morgenstern ◽  
Paul Field ◽  
Kalli Furtado ◽  
Jonny Williams ◽  
...  
Keyword(s):  
Southern Ocean ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Supercooled Liquid ◽  
Short Wave ◽  
Global Climate Models ◽  
Ice Crystals ◽  
Wave Radiation ◽  
Short Wave Radiation

Abstract. The present generation of global climate models is characterized by insufficient reflection of short-wave radiation over the Southern Ocean due to a misrepresentation of clouds. This is a significant concern as it leads to excessive heating of the ocean surface, sea surface temperature biases, and subsequent problems with atmospheric dynamics. In this study we modify cloud micro-physics in a recent version of the Met Office's Unified Model and show that choosing a more realistic value for the shape parameter of atmospheric ice-crystals, in better agreement with theory and observations, benefits the simulation of short-wave radiation. In the model, for calculating the growth rate of ice crystals through deposition, the default assumption is that all ice particles are spherical in shape. We modify this assumption to effectively allow for oblique shapes or aggregates of ice crystals. Along with modified ice nucleation temperatures, we achieve a reduction in the annual-mean short-wave cloud radiative effect over the Southern Ocean by up to 4 W/m2, and seasonally much larger reductions. By slowing the growth of the ice phase, the model simulates substantially more supercooled liquid cloud. We hypothesize that such abundant supercooled liquid cloud is the result of a paucity of ice nucleating particles in this part of the atmosphere.

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