scholarly journals Using Global and Regional Model Simulations to Understand Maritime Continent Wet‐Season Rainfall Variability

2018 ◽  
Vol 45 (22) ◽  
pp. 12,534-12,543
Author(s):  
Andrew D. King ◽  
Claire L. Vincent
Keyword(s):  
Rainfall Variability ◽  
Regional Model ◽  
Wet Season ◽  
Maritime Continent ◽  
Model Simulations

scholarly journals Improving Regional Model Simulations with Precipitation Assimilation

2005 ◽  
Vol 9 (20) ◽  
pp. 1-44 ◽  
Author(s):  
Ana M. B. Nunes ◽  
John O. Roads
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Regional Model ◽  
Seasonal Forecasts ◽  
Wet Season ◽  
Model Simulations ◽  
Precipitation Simulation ◽  
Global Reanalysis ◽  
Model Precipitation

Abstract Although large-scale atmospheric reanalyses are now providing physical, realistic fields for many variables, precipitation remains problematic. As shown in recent studies, using a regional model to downscale the global reanalysis only marginally alleviates the precipitation simulation problems. For this reason, later-generation analyses, including the recent National Centers for Environmental Prediction regional reanalysis, are using precipitation assimilation as a methodology to provide superior precipitation fields. This methodology can also be applied to regional model simulations to substantially improve the precipitation fields downscaled from global reanalysis. As an illustration of the regional model precipitation assimilation impact, the authors describe here an extended-range simulation comparison over South America. The numerical experiments cover the beginning of the Large-Scale Biosphere–Atmosphere wet season campaign of January 1999. Evaluations using radiosonde datasets obtained during this campaign are provided as well. As will be shown, rain-rate assimilation not only increases the regional model precipitation simulation skill but also provides improvements in other fields influenced by the precipitation. Because of the potential impact on land surface features, the authors believe they will ultimately be able to show improvements in monthly to seasonal forecasts when precipitation assimilation is used to generate more accurate land surface initial conditions.

ON REGIONAL MODEL SIMULATIONS OF CLIMATE CHANGE OVER NEW ZEALAND

1999 ◽  
Vol 19 ◽  
pp. 3 ◽  
Author(s):  
Renwick ◽  
Katzfey ◽  
McGregor ◽  
Nguyen
Keyword(s):  
Climate Change ◽  
New Zealand ◽  
Regional Model ◽  
Model Simulations

scholarly journals On the Sensitivity of the Simulated Diurnal Cycle of Precipitation to 3-Hourly Radiosonde Assimilation: A Case Study over the Western Maritime Continent

2021 ◽  
Vol 149 (10) ◽  
pp. 3449-3468
Author(s):  
Joshua Chun Kwang Lee ◽  
Anurag Dipankar ◽  
Xiang-Yu Huang
Keyword(s):  
Diurnal Cycle ◽  
High Frequency ◽  
Initial Conditions ◽  
Rainfall Variability ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Western Coast ◽  
Maritime Continent ◽  
Model Biases ◽  
Diurnal Cycle Of Precipitation

AbstractThe diurnal cycle is the most prominent mode of rainfall variability in the tropics, governed mainly by the strong solar heating and land–sea interactions that trigger convection. Over the western Maritime Continent, complex orographic and coastal effects can also play an important role. Weather and climate models often struggle to represent these physical processes, resulting in substantial model biases in simulations over the region. For numerical weather prediction, these biases manifest themselves in the initial conditions, leading to phase and amplitude errors in the diurnal cycle of precipitation. Using a tropical convective-scale data assimilation system, we assimilate 3-hourly radiosonde data from the pilot field campaign of the Years of Maritime Continent, in addition to existing available observations, to diagnose the model biases and assess the relative impacts of the additional wind, temperature, and moisture information on the simulated diurnal cycle of precipitation over the western coast of Sumatra. We show how assimilating such high-frequency in situ observations can improve the simulated diurnal cycle, verified against satellite-derived precipitation, radar-derived precipitation, and rain gauge data. The improvements are due to a better representation of the sea breeze and increased available moisture in the lowest 4 km prior to peak convection. Assimilating wind information alone was sufficient to improve the simulations. We also highlight how during the assimilation, certain multivariate background error constraints and moisture addition in an ad hoc manner can negatively impact the simulations. Other approaches should be explored to better exploit information from such high-frequency observations over this region.

scholarly journals Investigation of dominant hydrological processes in a tropical catchment in a monsoonal climate via the downward approach

2006 ◽  
Vol 10 (5) ◽  
pp. 769-782 ◽  
Author(s):  
L. Montanari ◽  
M. Sivapalan ◽  
A. Montanari
Keyword(s):  
Overland Flow ◽  
Soil Depth ◽  
Rainfall Variability ◽  
Sensitivity Analyses ◽  
Wet Season ◽  
Ungauged Catchments ◽  
Progressive Development ◽  
Total Runoff ◽  
High Storage Capacity ◽  
Streamflow Response

Abstract. This study explores the dominant processes that may be responsible for the observed streamflow response in Seventeen Mile Creek, a tropical catchment located in a monsoonal climate in Northern Territory, Australia. The hydrology of this vast region of Australia is poorly understood due to the low level of information and gauging that are available. Any insights that can be gained from the few well gauged catchments that do exist can be valuable for predictions and water resource assessments in other poorly gauged or ungauged catchments in the region. To this end, the available rainfall and runoff data from Seventeen Mile Creek catchment are analyzed through the systematic and progressive development and testing of rainfall-runoff models of increasing complexity, by following the "downward" or "top-down" approach. This procedure resulted in a multiple bucket model (4 buckets in parallel). Modelling results suggest that the catchment's soils and the landscape in general have a high storage capacity, generating a significant fraction of delayed runoff, whereas saturation excess overland flow occurs only after heavy rainfall events. The sensitivity analyses carried out with the model with regard to soil depth and temporal rainfall variability revealed that total runoff from the catchment is more sensitive to rainfall variations than to soil depth variations, whereas the partitioning into individual components of runoff appears to be more influenced by soil depth variations. The catchment exhibits considerable inter-annual variability in runoff volumes and the greatest determinant of this variability turns out to be the seasonality of the climate, the timing of the wet season, and temporal patterns of the rainfall. The water balance is also affected by the underlying geology, nature of the soils and the landforms, and the type, density and dynamics of vegetation, although information pertaining to these is lacking.

scholarly journals Likely Ranges of Climate Change in Bolivia

2013 ◽  
Vol 52 (6) ◽  
pp. 1303-1317 ◽  
Author(s):  
Christian Seiler ◽  
Ronald W. A. Hutjes ◽  
Pavel Kabat
Keyword(s):  
Climate Change ◽  
Amazon Basin ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Amazon Forest ◽  
Climate Change Scenarios ◽  
Wet Season ◽  
Global Circulation Models ◽  
The Andes ◽  
Interannual Rainfall Variability

AbstractBolivia is facing numerous climate-related threats, ranging from water scarcity due to rapidly retreating glaciers in the Andes to a partial loss of the Amazon forest in the lowlands. To assess what changes in climate may be expected in the future, 35 global circulation models (GCMs) from the third and fifth phases of the Coupled Model Intercomparison Project (CMIP3/5) were analyzed for the Bolivian case. GCMs were validated against observed surface air temperature, precipitation, and incoming shortwave (SW) radiation for the period 1961–90. Weighted ensembles were developed, and climate change projections for five emission scenarios were assessed for 2070–99. GCMs revealed an overall cold, wet, and positive-SW-radiation bias and showed no substantial improvement from the CMIP3 to the CMIP5 ensemble for the Bolivian case. Models projected an increase in temperature (2.5°–5.9°C) and SW radiation (1%–5%), with seasonal and regional differences. In the lowlands, changes in annual rainfall remained uncertain for CMIP3 whereas CMIP5 GCMs were more inclined to project decreases (−9%). This pattern also applied to most of the Amazon basin, suggesting a higher risk of partial biomass loss for the CMIP5 ensemble. Both ensembles agreed on less rainfall (−19%) during drier months (June–August and September–November), with significant changes in interannual rainfall variability, but disagreed on changes during wetter months (January–March). In the Andes, CMIP3 GCMs tended toward less rainfall (−9%) whereas CMIP5 tended toward more (+20%) rainfall during parts of the wet season. The findings presented here may provide inputs for studies of climate change impact that assess how resilient human and natural systems are under different climate change scenarios.

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