Monsoonal precipitation over Peninsular Malaysia in the CMIP6 HighResMIP experiments: the role of model resolution

AbstractThis study investigates the ability of 20 model simulations which contributed to the CMIP6 HighResMIP to simulate precipitation in different monsoon seasons and extreme precipitation events over Peninsular Malaysia. The model experiments utilize common forcing but are run with different horizontal and vertical resolutions. The impact of resolution on the models’ abilities to simulate precipitation and associated environmental fields is assessed by comparing multi-model ensembles at different resolutions with three observed precipitation datasets and four climate reanalyses. Model simulations with relatively high horizontal and vertical resolution exhibit better performance in simulating the annual cycle of precipitation and extreme precipitation over Peninsular Malaysia and the coastal regions. Improvements associated with the increase in horizontal and vertical resolutions are also found in the statistical relationship between precipitation and monsoon intensity in different seasons. However, the increase in vertical resolution can lead to a reduction of annual mean precipitation compared to that from the models with low vertical resolutions, associated with an overestimation of moisture divergence and underestimation of lower-tropospheric vertical ascent in the different monsoon seasons. This limits any improvement in the simulation of precipitation in the high vertical resolution experiments, particularly for the Southwest monsoon season.

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Monsoonal Precipitation Over Peninsular Malaysia in the CMIP6 Highresmip Experiments: The Role of Model Resolution

10.21203/rs.3.rs-741632/v1 ◽

2021 ◽

Author(s):

Ju Liang ◽

Mou Leong Tan ◽

Matthew Hawcroft ◽

Jennifer L. Catto ◽

Kevin I. Hodges ◽

...

Keyword(s):

Extreme Precipitation ◽

Monsoon Season ◽

Southwest Monsoon ◽

Peninsular Malaysia ◽

Vertical Resolution ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Different Seasons ◽

Model Ensembles ◽

The Impact

Abstract This study investigates the ability of 20 model simulations which contributed to the CMIP6 HighResMIP to simulate precipitation in different monsoon seasons and extreme precipitation events over Peninsular Malaysia. The model experiments utilize common forcing but are run with different horizontal and vertical resolutions. The impact of resolution on the models’ abilities to simulate precipitation and associated environmental fields is assessed by comparing multi-model ensembles at different resolutions with three observed precipitation datasets and four climate reanalyses. Model simulations with relatively high horizontal and vertical resolution exhibit better performance in simulating the annual cycle of precipitation and extreme precipitation over Peninsular Malaysia and the coastal regions. Improvements associated with the increase in horizontal and vertical resolutions are also found in the statistical relationship between precipitation and monsoon intensity in different seasons. However, the increase in vertical resolution can lead to a reduction of annual mean precipitation compared to that from the models with low vertical resolutions, associated with an overestimation of moisture divergence and underestimation of lower-tropospheric vertical ascent in the different monsoon seasons. This limits any improvement in the simulation of precipitation in the high vertical resolution experiments, particularly for the Southwest monsoon season.

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Changing seasonality of moderate and extreme precipitation events in the Alps

Natural Hazards and Earth System Science ◽

10.5194/nhess-18-2047-2018 ◽

2018 ◽

Vol 18 (7) ◽

pp. 2047-2056 ◽

Cited By ~ 20

Author(s):

Stefan Brönnimann ◽

Jan Rajczak ◽

Erich M. Fischer ◽

Christoph C. Raible ◽

Marco Rohrer ◽

...

Keyword(s):

Extreme Precipitation ◽

Climate Model ◽

Global Climate Model ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Rate Of Increase ◽

Decadal Scale ◽

The Future ◽

The Impact ◽

Precipitation Events

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius–Clapeyron relation, whereas weaker events or precipitation averages increase at a smaller rate than expected from the Clausius–Clapeyron relation. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present, and future. In order to make the data comparable, they are quantile mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 years and an increase of 10 %–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius–Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early autumn, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behaviour more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during the hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.

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Changing seasonality of moderate and extreme precipitation events in the Alps

10.5194/nhess-2018-55 ◽

2018 ◽

Author(s):

Stefan Brönnimann ◽

Jan Rajczak ◽

Erich Fischer ◽

Christoph C. Raible ◽

Marco Rohrer ◽

...

Keyword(s):

Extreme Precipitation ◽

Climate Model ◽

Global Climate Model ◽

Model Simulations ◽

Extreme Precipitation Events ◽

Rate Of Increase ◽

Decadal Scale ◽

The Future ◽

The Impact ◽

Precipitation Events

Abstract. The intensity of precipitation events is expected to increase in the future. The rate of increase depends on the strength or rarity of the events; very strong and rare events tend to follow the Clausius-Clapeyron relation, whereas weaker events or precipitation averages do not. An often overlooked aspect is seasonal occurrence of such events, which might change in the future. To address the impact of seasonality, we use a large ensemble of regional and global climate model simulations, comprising tens of thousands of model years of daily temperature and precipitation for the past, present and future. In order to make the data comparable, they are quantile-mapped to observation-based time series representative of the Aare catchment in Switzerland. Model simulations show no increase in annual maximum 1-day precipitation events (Rx1day) over the last 400 yrs and an increase of 10–20 % until the end of the century for a strong (RCP8.5) forcing scenario. This fits with a Clausius-Clapeyron scaling of temperature at the event day, which increases less than annual mean temperature. An important reason for this is a shift in seasonality. Rx1day events become less frequent in late summer and more frequent in early summer and early fall, when it is cooler. The seasonality shift is shown to be related to summer drying. Models with decreasing annual mean or summer mean precipitation show this behavior more strongly. The highest Rx1day per decade, in contrast, shows no change in seasonality in the future. This discrepancy implies that decadal-scale extremes are thermodynamically limited; conditions conducive to strong events still occur during hottest time of the year on a decadal scale. In contrast, Rx1day events are also limited by other factors. Conducive conditions are not reached every summer in the present, and even less so in the future. Results suggest that changes in the seasonal cycle need to be accounted for when preparing for moderately extreme precipitation events and assessing their socio-economic impacts.

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ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

Journal of Climate ◽

10.1175/2007jcli1705.1 ◽

2008 ◽

Vol 21 (1) ◽

pp. 22-39 ◽

Cited By ~ 48

Author(s):

Siegfried D. Schubert ◽

Yehui Chang ◽

Max J. Suarez ◽

Philip J. Pegion

Keyword(s):

United States ◽

West Coast ◽

Extreme Precipitation ◽

East Coast ◽

Daily Precipitation ◽

Precipitation Variability ◽

The West ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

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Extreme precipitation events during the South Asian summer monsoon season in the past century

10.5194/egusphere-egu21-6418 ◽

2021 ◽

Author(s):

Renaud Falga ◽

Chien Wang

Keyword(s):

South Asian ◽

Extreme Events ◽

Extreme Precipitation ◽

Monsoon Season ◽

Past Century ◽

South Asian Summer Monsoon ◽

The South ◽

The Past ◽

Extreme Precipitation Events ◽

Precipitation Events

The South Asian monsoon system impacts the livelihoods of over a billion people. While the overall monsoon rainfall is believed to have decreased during the 20th century, there is a good agreement that the extreme precipitation events have been rising in some parts of India. As an important part of the Indian population is dependent on rainfed agriculture, such a rise in extremes, along with resulting flood events, can be all the more problematic. Although studies tend to link this rise in extreme events with anthropogenic forcing, some uncertainties remain on the exact causes. In order to examine the correlation between anthropogenic forcings and the different trends in extreme events, we have analyzed the high-resolution daily rainfall data in the past century delivered by the Indian Meteorological Department alongside several other economic and ecological estimates. The results from this analysis will be presented in detail.

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Spatial and Temporal Analysis of Precipitation Extremities of Eastern Nepal in the Last Two Decades (1997–2016)

10.5194/egusphere-egu2020-2784 ◽

2020 ◽

Author(s):

Sunil Subba ◽

Yaoming Ma ◽

Weiqiang Ma

Keyword(s):

Climate Change ◽

Extreme Events ◽

Extreme Precipitation ◽

Tropical Rainfall Measuring Mission ◽

Heavy Precipitation ◽

Temporal Analysis ◽

Extreme Precipitation Events ◽

Slope Estimator ◽

The Impact ◽

Precipitation Events

In recent days there have been discussions regarding the impact of climate change and its vagaries of the weather, particularly concerning extreme events. Nepal, being a mountainous country, is more susceptible to precipitation extreme events and related hazards, which hinder the socioeconomic development of the nation. In this regard, this study aimed to address this phenomenon for one of the most naturally and socioeconomically important regions of Nepal, namely, Eastern Nepal. The data were collected for the period of 1997 to 2016. The interdecadal comparison for two periods (1997&#8211;2006 and 2007&#8211;2016) was maintained for the calculation of extreme precipitation indices as per recommended by Expert Team on Climate Change Detection and Indices. Linear trends were calculated by using Mann&#8208;Kendall and Sen's Slope estimator. The average annual precipitation was found to be decreasing at an alarming rate of &#8722;20 mm/year in the last two decades' tenure. In case of extreme precipitation events, consecutive dry days, one of the frequency indices, showed a solo increase in its trend (mostly significant). Meanwhile, all the intensity indices of extreme precipitation showed decreasing trends (mostly insignificant). Thus, it can be concluded that Eastern Nepal has witnessed some significant drier days in the last two decades, as the events of heavy, very heavy, extremely heavy precipitation events, and annual wet day precipitation (PRCPTOT) were found to be decreasing. The same phenomena were also seen in the Tropical Rainfall Measuring Mission 3B42 V7 satellite precipitation product for whole Nepal.

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Spatial Distribution of Picophytoplankton in Southeastern Coast of Peninsular Malaysia Using Flow Cytometry

Pertanika Journal of Science and Technology ◽

10.47836/pjst.29.3.18 ◽

2021 ◽

Vol 29 (3) ◽

Author(s):

Roswati Md Amin ◽

Md Suffian Idris ◽

Nurul Asmera Mudiman ◽

Noor Hazwani Mohd Azmi ◽

Hing Lee Siang

Keyword(s):

Flow Cytometry ◽

Spatial Distribution ◽

Distribution Patterns ◽

Southwest Monsoon ◽

Peninsular Malaysia ◽

Percentage Contribution ◽

Southeastern Coast ◽

Ocean Productivity ◽

The Impact

The distribution of picocyanobacteria from two genera, Synechococcus and Prochlorococcus, and picoeukaryotes in surface water (0.5 m) was investigated by flow cytometry in the southeastern coast of Peninsular Malaysia during the Southwest monsoon in August 2014. During the cruise, Synechococcus cells were predominant throughout the study area, contributing as much as 50% to the total picophytoplankton population, whereas picoeukaryotes and Prochlorococcus constituted only 31% and 19% of the population, respectively. Spatially, Synechococcus and picoeukaryotes were more dominant in coastal waters, while Prochlorococcus appeared to be more highly abundant in offshore waters. Furthermore, the percentage contribution of each population to total picophytoplankton also exhibited different spatial distribution patterns along a coastal-offshore gradient. The percentage contribution of Synechococcus was spatially constant throughout the study area, while the fraction contributed by picoeukaryotes showed a reduced contribution from coastal to offshore waters. In contrast, Prochlorococcus exhibited an increased proportion to total picophytoplankton across a coastal-offshore gradient, suggesting the increasing importance of this population in offshore waters of the study area. As revealed by Canonical Correlation Analysis, the abundance of Synechococcus and picoeukaryotes increased significantly with reducing dissolved oxygen levels and pH, and with increasing total chlorophyll. In contrast, temperature was the only factor influencing the abundance of Prochlorococcus significantly increased with decreasing water temperature in the study area. Overall, results of the present study provide valuable information on the role of regional environmental factors in the distribution and dominance of picophytoplankton communities that are not only critical for the ocean productivity but also the impact on the carbon cycle in the study area.

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On the links between sub-seasonal clustering of extreme precipitation and high discharge in Switzerland and Europe

10.5194/hess-2021-625 ◽

2021 ◽

Author(s):

Alexandre Tuel ◽

Bettina Schaefli ◽

Jakob Zscheischler ◽

Olivia Martius

Keyword(s):

Extreme Precipitation ◽

Temporal Structure ◽

Extreme Precipitation Event ◽

Precipitation Event ◽

Discharge Data ◽

High Discharge ◽

Temporal Clustering ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract. River discharge is impacted by the sub-seasonal (weekly to monthly) temporal structure of precipitation. One example is the successive occurrence of extreme precipitation events over sub-seasonal timescales, referred to as temporal clustering. Its potential effects on discharge have received little attention. Here, we address this question by analysing discharge observations following extreme precipitation events either clustered in time or occurring in isolation. We rely on two sets of precipitation and discharge data, one centered on Switzerland and the other over Europe. We identify "clustered" extreme precipitation events based on the previous occurrence of another extreme precipitation within a given time window. We find that clustered events are generally followed by a more prolonged discharge response with a larger amplitude. The probability of exceeding the 95th discharge percentile in the five days following an extreme precipitation event is in particular up to twice as high for situations where another extreme precipitation event occurred in the preceding week compared to isolated extreme precipitation events. The influence of temporal clustering decreases as the clustering window increases; beyond 6–8 weeks the difference with non-clustered events is negligible. Catchment area, streamflow regime and precipitation magnitude also modulate the response. The impact of clustering is generally smaller in snow-dominated and large catchments. Additionally, particularly persistent periods of high discharge tend to occur in conjunction with temporal clusters of precipitation extremes.

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Sensitivity of Heavy Precipitation Forecasts to Small Modifications of Large-Scale Weather Patterns for the Elbe River

Journal of Hydrometeorology ◽

10.1175/2010jhm1186.1 ◽

2010 ◽

Vol 11 (3) ◽

pp. 770-780 ◽

Cited By ~ 10

Author(s):

Ingo Schlüter ◽

Gerd Schädler

Keyword(s):

Extreme Precipitation ◽

Large Scale ◽

Spatiotemporal Variability ◽

Small Scale ◽

Synoptic Situation ◽

Flood Events ◽

Weather Patterns ◽

Extreme Precipitation Events ◽

The Impact ◽

Precipitation Events

Abstract Extreme flood events are caused by long-lasting and/or intensive precipitation. The detailed knowledge of the distribution, intensity, and spatiotemporal variability of precipitation is, therefore, a prerequisite for hydrological flood modeling and flood risk management. For hydrological modeling, temporal and spatial high-resolution precipitation data can be provided by meteorological models. This study deals with the question of how small changes in the synoptic situation affect the characteristics of extreme forecasts. For that purpose, two historic extreme precipitation events were hindcasted using the Consortium for Small Scale Modeling (COSMO) model of the German Weather Service (DWD) with different grid resolutions (28, 7, and 2.8 km), where the domains with finer resolutions were nested into the ones with coarser resolution. The results show that the model is capable of simulating such extreme precipitation events in a satisfactory way. To assess the impact of small changes in the synoptic situations on extreme precipitation events, the large-scale atmospheric fields were shifted to north, south, east, and west with respect to the orography by about 28 and 56 km, respectively, in one series of runs while in another series, the relative humidity and temperature were increased to modify the amount of precipitable water. Both series were performed for the Elbe flood events in August 2002 and January 2003, corresponding to two very different synoptic situations. The results show that the modeled precipitation can be quite sensitive to small changes of the synoptic situation with changes in the order of 20% for the maximum daily precipitation and that the types of synoptic situations play an important role. While van Bebber weather conditions, of Mediterranean origin, were quite sensitive to modifications, more homogeneous weather patterns were less sensitive.

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The implications of soil erosion model conceptualization, bias-correction methods and climate model ensembles on soil erosion projections under climate change

10.5194/egusphere-egu2020-8158 ◽

2020 ◽

Author(s):

Joris de Vente ◽

Joris Eekhout

Keyword(s):

Climate Change ◽

Soil Erosion ◽

Extreme Precipitation ◽

Climate Models ◽

Climate Model ◽

Erosion Model ◽

Distribution Mapping ◽

Climate Model Ensembles ◽

Model Ensembles ◽

The Impact

Climate models project increased extreme precipitation for the coming decades, which may lead to higher soil erosion in many locations worldwide. The impact of climate change on soil erosion is most often assessed by applying a soil erosion model forced by bias-corrected climate model output. A literature review among more than 100 papers showed that many studies use different soil erosion models, bias-correction methods and climate model ensembles. In this study, we assessed how these differences affect the outcome of climate change impact assessments on soil erosion. The study was performed in two contrasting Mediterranean catchments (SE Spain), where climate change is projected to lead to a decrease in annual precipitation sum and an increase in extreme precipitation, based on the RCP8.5 emission scenario. First, we assessed the impact of soil erosion model selection using the three most widely used model concepts, i.e. a model forced by precipitation (RUSLE), a model forced by runoff (MUSLE), and a model forced by precipitation and runoff (MMF). Depending on the model, soil erosion in the study area is projected to decrease (RUSLE) or increase (MUSLE and MMF). The differences between the model projections are inherently a result of their model conceptualization, such as a decrease of soil loss due to decreased annual precipitation sum (RUSLE) and an increase of soil loss due to increased extreme precipitation and, consequently, increased runoff (MUSLE). An intermediate result is obtained with MMF, where a projected decrease in detachment by raindrop impact is counteracted by a projected increase in detachment by runoff. Second, we evaluated the implications of three bias&#8208;correction methods, i.e. delta change, quantile mapping and scaled distribution mapping. Scaled distribution mapping best reproduces the raw climate change signal, in particular for extreme precipitation. Depending on the bias&#8208;correction method, soil erosion is projected to decrease (delta change) or increase (quantile mapping and scaled distribution mapping). Finally, we assessed the effect of climate model ensembles on soil erosion projections. We showed that individual climate models may project opposite changes with respect to the ensemble average, hence, climate model ensembles are essential in soil erosion impact assessments to account for climate model uncertainty. We conclude that in climate change impact assessments it is important to select a soil erosion model that is forced by both precipitation and runoff, which under climate change may have a contrasting effect on soil erosion. Furthermore, the impact of climate change on soil erosion can only accurately be assessed with a bias&#8208;correction method that best reproduces the projected climate change signal, in combination with a representative ensemble of climate models.

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