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Gridded rainfall products could augment the shortage of available rainfall data in archipelagic countries like the Philippines, where weather stations are still sparsely distributed especially over its remote and lessdeveloped islands. However, these products need to be validated first using ground measurements to determine their ability to represent properties of local rainfall. This study compares four high-resolution, gridded datasets--APHRODITEv1101, CHIRPSv2, TRMM 3B42v7, and PERSIANN-CDR--with respect to 49 synoptic weather stations over the Philippines from 1998 to 2005. The performance of these datasets was assessed in terms of bias, distribution, and different statistical error metrics and skill scores across time scales and climate types. Results show that all the datasets were able to capture the basic climatology and to varying extents, spatial patterns of Philippine rainfall. TRMM 3B42v7 has the least overall average monthly bias and most closely resembles the rainfall distribution observed at weather stations, especially dry days and torrential rain days for the whole Philippines.APHRODITEv1101 performs best in terms of errormetrics and skill scores but displays consistent underestimates. CHIRPSv2, on the other hand, best captures the seasonal rainfall peaks in the different climate types in the Philippines but is prone to larger errors. Last, PERSIANN-CDR shows generally poormetrics and rainfall distributions, in comparison to the other datasets. These key findings are used to identify possible research applications in the Philippines that are best suited for each dataset. [ABSTRACT FROM AUTHOR]

Several sets of reference regions have been proposed in the literature for the regional synthesis of observed and model-projected climate change information. A popular example is the set of reference regions introduced in the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX) based on a prior coarser selection and then slightly modified for the 5th Assessment Report of the IPCC. This set was developed for reporting sub-continental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes (the typical resolution of the 5th Climate Model Intercomparison Projection, CMIP5, climate models was around 2º). These regions have been used as the basis for several popular spatially aggregated datasets, such as the seasonal mean temperature and precipitation in IPCC regions for CMIP5. Here we present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher model resolution (around 1º for CMIP6). As a result, the number of regions increased to 43 land plus 12 open ocean, better representing consistent regional climate features. The paper describes the rationale followed for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and shapefile together with companion R and Python notebooks to illustrate their use in practical problems (trimming data, etc.). We also describe the generation of a new dataset with monthly temperature and precipitation spatially aggregated in the new regions, currently for CMIP5 (for backwards consistency) and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter diagrams to offer guidance on the likely range of future climate change at the scale of reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository; https://github.com/SantanderMetGroup/ATLAS, doi:10.5281/zenodo.3688072 (Iturbide et al., 2020). [ABSTRACT FROM AUTHOR]

This paper highlights detailed projected changes in rainfall over Thailand for the early (2011–2040), middle (2041–2070) and late (2071–2099) periods of the 21st century under the representative concentration pathways (RCP) 4.5 and RCP 8.5 using the high‐resolution multi‐model simulations of the Coordinated Regional Climate Downscaling Experiment (CORDEX) Southeast Asia. The ensemble mean is calculated based on seven members consisting of six general circulation models (GCMs) and three regional climate models (RCMs). Generally, the ensemble mean precipitation agrees reasonably well with observations, best represented by the Global Precipitation Climatology Center (GPCC) data, over Thailand during the historical period (1976–2005). However, inter‐model variations can be large among ensemble members especially during dry months (December to March) for northern‐central‐eastern parts, and throughout the year for the southern parts of Thailand. Similarly for future projection periods, inter‐model variations in the sign and magnitude of changes exist. The ensemble means of projected changes in rainfall for both RCPs during dry months show distinct contrast between the northern‐central‐eastern parts and the southern parts of Thailand with generally wetter and drier conditions, respectively. The magnitude of change can be as high as 15% of the historical period, which varies depending on the sub‐region, season, projection period, and RCP scenario. In contrast, generally drier conditions are projected during the wet season (June to September) throughout the country for both RCPs where the rainfall reduction can be as high as 10% in some areas. However, the magnitude of projected rainfall changes of some individual models can be much larger than the ensemble means, exceeding 40% in some cases. These projected changes are related to the changes in regional circulations associated with the winter and summer monsoons, which are projected to weaken. The drier (wetter) condition is associated with the enhanced subsidence (rising motion). [ABSTRACT FROM AUTHOR]

The Quantile Mapping (QM) bias correction (BC) technique was applied for the first time to address biases in the simulated precipitation over Vietnam from the Regional Climate Model (RegCM) driven by five Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Climate Model (GCM) products. The QM process was implemented for the period 1986-2005, and subsequently applied to the mid-future period 2046-2065 under both Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. Comparison with the original model outputs during the independent validation period shows a large bias reduction from 45% to 3% over Vietnam and significant improvements in representing precipitation indices (PI) after applying the QM technique. Moreover, the ensemble average of the BC products generally performed better than an individual BC member in capturing the spatial distribution of the PIs. A drier condition with a longer rainfall break, and shorter consecutive rainfall events are anticipated over Northern and Central Vietnam during their respective wet seasons in the mid-future. Furthermore, this study showed that the QM method minimally modified the future changes in PIs over most of Vietnam; thus, these corrected projections could be used in climate impacts and adaptation studies. [ABSTRACT FROM AUTHOR]

To meet the growing demand for climate change information to guide national and local adaptation decision-making in the Philippines, the climate science and services community is producing an increasing volume of future climate data using a range of modelling approaches. However, there is a significant methodological challenge in how to best compare and combine information produced using different models and methods. In this paper, we present the landscape of climate model data available in the Philippines and show how multi-model, multi-method climate projections are being used and communicated to inform climate change policy and planning, focusing on the agriculture sector. We highlight the importance of examining and communicating methodological strengths and weaknesses as well as understanding the needs and capabilities of different user communities. We discuss the assessment of projections from different methods, including global and regional downscaled simulations, and discuss ways to summarise and communicate this information to stakeholders using co-production approaches. The paper concludes with perspectives on how to best use an “ensemble of opportunity” to construct defensible, plausible and usable climate projections. [ABSTRACT FROM AUTHOR]

Regional climate models have been useful in climate studies and in downscaling climate projections from global climate models, especially for areas characterized by complex topography and coastline features, such as the Philippines. However, several factors may affect model skill, such as uncertainties related to the boundary conditions and model configuration. This study evaluates the performance of the non-hydrostatic regional climate model (NHRCM) over the Philippines. Present-day climate simulations at 50 km resolution are conducted using two sets of boundary conditions (ECMWF ERA-Interim and the NCEP/NCAR Reanalysis Project NNRP1), as well as two convective parameterization schemes in the model (Grell and Kain-Fritsch). Results show that the seasonal changes in the spatial distribution of temperature, rainfall, and winds over the Philippines are simulated reasonably well. NHRCM has an overall cold and dry bias over land, the degree of which depends on the boundary condition and the convective scheme used. After adjusting the simulated temperature because of the difference in topography, the temperature differs from that observed by -0.90℃ to -0.42℃ on average. The rainfall bias in NHRCM ranges from -62.13% to -25.20%. Regardless of the boundary condition, the Grell scheme results in the lowest temperature bias with high skill scores, while the Kain-Fritsch scheme gives the lowest rainfall bias with high correlation and skill scores. The boundary conditions also influence model skill, such that the model bias is lower for temperature when ERA-Interim is used, but lower for rainfall with NNRP1. NHRCM represents the seasonal cycles of temperature and rainfall for all regions, but tends to generate more occurrences of cold and dry months. Improvements in the model are still possible, but these results indicate the potential of the model to be used for providing essential information for describing historical and future changes in the Philippine climate. [ABSTRACT FROM AUTHOR]

This study examines the projected precipitation extremes for the end of 21st century (2081–2100) over Southeast Asia (SEA) using the output of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (SEACLID/CORDEX-SEA). Eight ensemble members, representing a subset of archived CORDEX-SEA simulations at 25 km spatial resolution, were examined for emission scenarios of RCP4.5 and RCP8.5. The study utilised four different indicators of rainfall extreme, i.e. the annual/seasonal rainfall total (PRCPTOT), consecutive dry days (CDD), frequency of extremely heavy rainfall (R50mm) and annual/seasonal maximum of daily rainfall (RX1day). In general, changes in extreme indices are more pronounced and covering wider area under RCP8.5 than RCP4.5. The decrease in annual PRCPTOT is projected over most of SEA region, except for Myanmar and Northern Thailand, with magnitude as much as 20% (30%) under RCP4.5 (RCP8.5) scenario. The most significant and robust changes were noted in CDD, which is projected to increase by as much as 30% under RCP4.5 and 60% under RCP8.5, particularly over Maritime Continent (MC). The projected decrease in PRCPTOT over MC is significant and robust during June to August (JJA) and September to November (SON). During March to May (MAM) under RCP8.5, significant and robust PRCPTOT decreases are also projected over Indochina. The CDD changes during JJA and SON over MC are even higher, more robust and significant compared to the annual changes. At the same time, a wetting tendency is also projected over Indochina. The R50mm and RX1day are projected to increase, during all seasons with significant and robust signal of RX1day during JJA and SON. • Future changes of Southeast Asia precipitation extremes were examined. • The result was derived from the CORDEX-SEA simulations experiments. • The dry tendency is projected over the maritime continent. • Increasing extreme rainfall frequency and intensity over the mainland Indo-China. • Significant and robust change signals during JJA and SON. [ABSTRACT FROM AUTHOR]