scholarly journals Downscaling of Seasonal Rainfall over the Philippines: Dynamical versus Statistical Approaches

2012 ◽  
Vol 140 (4) ◽  
pp. 1204-1218 ◽  
Author(s):  
Andrew W. Robertson ◽  
Jian-Hua Qian ◽  
Michael K. Tippett ◽  
Vincent Moron ◽  
Anthony Lucero

The additional value derived from a regional climate model (RCM) nested within general circulation model (GCM) seasonal simulations, over and above statistical methods of downscaling, is compared over the Philippines for the April–June monsoon transition season. Spatial interpolation of RCM and GCM gridbox values to station locations is compared with model output statistics (MOS) correction. The anomaly correlation coefficient (ACC) skill at the station scale of seasonal total rainfall is somewhat higher in the RCM compared to the GCM when using spatial interpolation. However, the ACC skills obtained using MOS of the GCM or RCM wind fields are shown to be generally—and rather equally—superior. The ranked probability skill scores (RPSS) are also generally much higher when using MOS, with slightly higher scores in the GCM case. Very high skills were found for MOS correction of daily rainfall frequency as a function of GCM and RCM seasonal-average low-level wind fields, but with no apparent advantage from the RCM. MOS-corrected monsoon onset dates often showed skill values similar to those of seasonal rainfall total, with good skill over the central Philippines. Finally, it is shown that the MOS skills decrease markedly and become inferior to those of spatial interpolation when the length of the 28-yr training set is halved. The results may be region dependent, and the excellent station data coverage and strong impact of ENSO on the Philippines may be factors contributing to the good MOS performance when using the full-length dataset over the Philippines.

2006 ◽  
Vol 19 (16) ◽  
pp. 3903-3931 ◽  
Author(s):  
H. Schmidt ◽  
G. P. Brasseur ◽  
M. Charron ◽  
E. Manzini ◽  
M. A. Giorgetta ◽  
...  

Abstract This paper introduces the three-dimensional Hamburg Model of the Neutral and Ionized Atmosphere (HAMMONIA), which treats atmospheric dynamics, radiation, and chemistry interactively for the height range from the earth’s surface to the thermosphere (approximately 250 km). It is based on the latest version of the ECHAM atmospheric general circulation model of the Max Planck Institute for Meteorology in Hamburg, Germany, which is extended to include important radiative and dynamical processes of the upper atmosphere and is coupled to a chemistry module containing 48 compounds. The model is applied to study the effects of natural and anthropogenic climate forcing on the atmosphere, represented, on the one hand, by the 11-yr solar cycle and, on the other hand, by a doubling of the present-day concentration of carbon dioxide. The numerical experiments are analyzed with the focus on the effects on temperature and chemical composition in the mesopause region. Results include a temperature response to the solar cycle by 2 to 10 K in the mesopause region with the largest values occurring slightly above the summer mesopause. Ozone in the secondary maximum increases by up to 20% for solar maximum conditions. Changes in winds are in general small. In the case of a doubling of carbon dioxide the simulation indicates a cooling of the atmosphere everywhere above the tropopause but by the smallest values around the mesopause. It is shown that the temperature response up to the mesopause is strongly influenced by changes in dynamics. During Northern Hemisphere summer, dynamical processes alone would lead to an almost global warming of up to 3 K in the uppermost mesosphere.


2015 ◽  
Vol 15 (10) ◽  
pp. 5537-5555 ◽  
Author(s):  
R. Eichinger ◽  
P. Jöckel ◽  
S. Brinkop ◽  
M. Werner ◽  
S. Lossow

Abstract. This modelling study aims at an improved understanding of the processes that determine the water vapour budget in the stratosphere by means of the investigation of water isotope ratios. An additional (and separate from the actual) hydrological cycle has been introduced into the chemistry–climate model EMAC, including the water isotopologues HDO and H218O and their physical fractionation processes. Additionally an explicit computation of the contribution of methane oxidation to H2O and HDO has been incorporated. The model expansions allow detailed analyses of water vapour and its isotope ratio with respect to deuterium throughout the stratosphere and in the transition region to the troposphere. In order to assure the correct representation of the water isotopologues in the model's hydrological cycle, the expanded system has been evaluated in several steps. The physical fractionation effects have been evaluated by comparison of the simulated isotopic composition of precipitation with measurements from a ground-based network (GNIP) and with the results from the isotopologue-enabled general circulation model ECHAM5-wiso. The model's representation of the chemical HDO precursor CH3D in the stratosphere has been confirmed by a comparison with chemical transport models (1-D, CHEM2D) and measurements from radiosonde flights. Finally, the simulated stratospheric HDO and the isotopic composition of water vapour have been evaluated, with respect to retrievals from three different satellite instruments (MIPAS, ACE-FTS, SMR). Discrepancies in stratospheric water vapour isotope ratios between two of the three satellite retrievals can now partly be explained.


2009 ◽  
Vol 137 (9) ◽  
pp. 2851-2868 ◽  
Author(s):  
Masaru Inatsu ◽  
Masahide Kimoto

Abstract This study newly developed the interactively nested climate model (INCL) using a general circulation model (GCM) interactively nested with a regional atmospheric model (RAM). One interactive experiment with finer RAM topography and another with coarser topography, as well as offline versions of each experiment, were performed to investigate the effects of subsynoptic-scale eddies and subsynoptic-scale mountains in northeast Asia on the larger-scale climate, using the GCM with T42 atmosphere and the RAM with 40-km mesh size in the INCL system. The subsynoptic-scale eddy effect restrictively increased synoptic-scale eddy activity within the RAM domain. In contrast, subsynoptic-scale mountains had the effect of robust anticyclonic circulation around the Sea of Japan and effectively forced larger-scale circulation. The effect was positively fed back to the mean field and amplified the anticyclonic circulation accompanied by suppressed storm activity in northeast Asia. The results suggest that subsynoptic-scale mountains affect not only subsynoptic-scale eddies but also the global climate.


2011 ◽  
Vol 4 (4) ◽  
pp. 3047-3065
Author(s):  
R. S. Smith

Abstract. FAMOUS is an ocean-atmosphere general circulation model of low resolution, based on version 4.5 of the UK MetOffice Unified Model. Here we update the model description to account for changes in the model as it is used in the CMIP5 EMIC model intercomparison project (EMICmip) and a number of other studies. Most of these changes correct errors found in the code. The EMICmip version of the model (XFXWB) has a better-conserved water budget and additional cooling in some high latitude areas, but otherwise has a similar climatology to previous versions of FAMOUS. A variant of XFXWB is also described, with changes to the dynamics at the top of the model which improve the model climatology (XFHCC).


2017 ◽  
Vol 24 (4) ◽  
pp. 681-694 ◽  
Author(s):  
Yuxin Zhao ◽  
Xiong Deng ◽  
Shaoqing Zhang ◽  
Zhengyu Liu ◽  
Chang Liu ◽  
...  

Abstract. Climate signals are the results of interactions of multiple timescale media such as the atmosphere and ocean in the coupled earth system. Coupled data assimilation (CDA) pursues balanced and coherent climate analysis and prediction initialization by incorporating observations from multiple media into a coupled model. In practice, an observational time window (OTW) is usually used to collect measured data for an assimilation cycle to increase observational samples that are sequentially assimilated with their original error scales. Given different timescales of characteristic variability in different media, what are the optimal OTWs for the coupled media so that climate signals can be most accurately recovered by CDA? With a simple coupled model that simulates typical scale interactions in the climate system and twin CDA experiments, we address this issue here. Results show that in each coupled medium, an optimal OTW can provide maximal observational information that best fits the characteristic variability of the medium during the data blending process. Maintaining correct scale interactions, the resulting CDA improves the analysis of climate signals greatly. These simple model results provide a guideline for when the real observations are assimilated into a coupled general circulation model for improving climate analysis and prediction initialization by accurately recovering important characteristic variability such as sub-diurnal in the atmosphere and diurnal in the ocean.


2007 ◽  
Vol 4 (5) ◽  
pp. 3413-3440 ◽  
Author(s):  
E. P. Maurer ◽  
H. G. Hidalgo

Abstract. Downscaling of climate model data is essential to most impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km² per grid cell) resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscaling (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit some skill in reproducing both observed wet and dry extremes and the difference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the reanalysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demonstrates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day correspondence of weather from the GCM needs to be reproduced for some applications. The ability to produce skillful downscaled daily data depends primarily on the ability of the climate model to show daily skill.


Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.


2014 ◽  
Vol 27 (24) ◽  
pp. 9197-9213 ◽  
Author(s):  
Michael Horn ◽  
Kevin Walsh ◽  
Ming Zhao ◽  
Suzana J. Camargo ◽  
Enrico Scoccimarro ◽  
...  

Abstract Future tropical cyclone activity is a topic of great scientific and societal interest. In the absence of a climate theory of tropical cyclogenesis, general circulation models are the primary tool available for investigating the issue. However, the identification of tropical cyclones in model data at moderate resolution is complex, and numerous schemes have been developed for their detection. The influence of different tracking schemes on detected tropical cyclone activity and responses in the Hurricane Working Group experiments is examined herein. These are idealized atmospheric general circulation model experiments aimed at determining and distinguishing the effects of increased sea surface temperature and other increased CO2 effects on tropical cyclone activity. Two tracking schemes are applied to these data and the tracks provided by each modeling group are analyzed. The results herein indicate moderate agreement between the different tracking methods, with some models and experiments showing better agreement across schemes than others. When comparing responses between experiments, it is found that much of the disagreement between schemes is due to differences in duration, wind speed, and formation-latitude thresholds. After homogenization in these thresholds, agreement between different tracking methods is improved. However, much disagreement remains, accountable for by more fundamental differences between the tracking schemes. The results indicate that sensitivity testing and selection of objective thresholds are the key factors in obtaining meaningful, reproducible results when tracking tropical cyclones in climate model data at these resolutions, but that more fundamental differences between tracking methods can also have a significant impact on the responses in activity detected.


2013 ◽  
Vol 13 (22) ◽  
pp. 11221-11234 ◽  
Author(s):  
F. Arfeuille ◽  
B. P. Luo ◽  
P. Heckendorn ◽  
D. Weisenstein ◽  
J. X. Sheng ◽  
...  

Abstract. In terms of atmospheric impact, the volcanic eruption of Mt. Pinatubo (1991) is the best characterized large eruption on record. We investigate here the model-derived stratospheric warming following the Pinatubo eruption as derived from SAGE II extinction data including recent improvements in the processing algorithm. This method, termed SAGE_4λ, makes use of the four wavelengths (385, 452, 525 and 1024 nm) of the SAGE II data when available, and uses a data-filling procedure in the opacity-induced "gap" regions. Using SAGE_4λ, we derived aerosol size distributions that properly reproduce extinction coefficients also at much longer wavelengths. This provides a good basis for calculating the absorption of terrestrial infrared radiation and the resulting stratospheric heating. However, we also show that the use of this data set in a global chemistry–climate model (CCM) still leads to stronger aerosol-induced stratospheric heating than observed, with temperatures partly even higher than the already too high values found by many models in recent general circulation model (GCM) and CCM intercomparisons. This suggests that the overestimation of the stratospheric warming after the Pinatubo eruption may not be ascribed to an insufficient observational database but instead to using outdated data sets, to deficiencies in the implementation of the forcing data, or to radiative or dynamical model artifacts. Conversely, the SAGE_4λ approach reduces the infrared absorption in the tropical tropopause region, resulting in a significantly better agreement with the post-volcanic temperature record at these altitudes.


2012 ◽  
Vol 12 (12) ◽  
pp. 5367-5390 ◽  
Author(s):  
J. Kelly ◽  
P. A. Makar ◽  
D. A. Plummer

Abstract. Ten year simulations of North American current and future air-quality were carried out using a regional air-quality model driven by a regional climate model, in turn driven by a general circulation model. Three separate summer scenarios were performed: a scenario representing the years 1997 to 2006, and two SRES A2 climate scenarios for the years 2041 to 2050. The first future climate scenario makes use of 2002 anthropogenic precursor emissions, and the second applied emissions scaling factors derived from the IPCC Representative Concentration Pathway 6 (RCP 6) scenario to estimate emissions for 2050 from existing 2020 projections. Ten-year averages of ozone and PM2.5 at North American monitoring network stations were used to evaluate the model's current chemical climatology. The model was found to have a similar performance for ozone as when driven by an operational weather forecast model. The PM2.5 predictions had larger negative biases, likely resulting from the absence of rainwater evaporation, and from sub-regional negative biases in the surface temperature fields, in the version of the climate model used here. The differences between the two future climate simulations and the current climate simulation were used to predict the changes to air-quality that might be expected in a future warmer climate, if anthropogenic precursor emissions remain constant at their current levels, versus if the RCP 6 emissions controls were adopted. Metrics of concentration, human health, and ecosystem damage were compared for the simulations. The scenario with future climate and current anthropogenic emissions resulted in worse air-quality than for current conditions – that is, the effect of climate-change alone, all other factors being similar, would be a worsening of air-quality. These effects are spatially inhomogeneous, with the magnitude and sign of the changes varying with region. The scenario with future climate and RCP 6 emissions for 2050 resulted in an improved air-quality, with decreases in key pollutant concentrations, in acute human mortality associated with air-pollution, and in sulphur and ozone deposition to the ecosystem. The positive outcomes of the RCP 6 emissions reductions were found to be of greater magnitude than the negative outcomes of climate change alone. The RCP 6 scenario however resulted in an increase in the deposition of nitrogen, as a result of increased ammonia emissions expected in that scenario, compared to current ammonia emissions levels. The results of the study raise the possibility that simultaneous reductions of greenhouse gases and air pollution precursors may further reduce air pollution levels, with the added benefits of an immediate reduction in the impacts of air pollution on human and ecosystem health. Further scenarios to investigate this possibility are therefore recommended.


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