scholarly journals Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5

2020 ◽  
Vol 13 (11) ◽  
pp. 5147-5173
Author(s):  
Jaeyoung Song ◽  
Gretchen R. Miller ◽  
Anthony T. Cahill ◽  
Luiza Maria T. Aparecido ◽  
Georgianne W. Moore
Keyword(s):  
Costa Rica ◽  
Land Surface ◽  
Carbon Flux ◽  
Complex Terrain ◽  
Aerodynamic Resistance ◽  
Mean Annual Precipitation ◽  
Leaf Wetness ◽  
Rainfall Events ◽  
Vapor Flux ◽  
Mountainous Regions

Abstract. This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulations for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micrometeorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5, but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLMs still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.

scholarly journals Modeling land surface processes over a mountainous rainforest in Costa Rica using CLM4.5 and CLM5

2020 ◽  
Author(s):  
Jaeyoung Song ◽  
Gretchen R. Miller ◽  
Anthony T. Cahill ◽  
Luiza Aparecido ◽  
Georgianne W. Moore
Keyword(s):  
Costa Rica ◽  
Land Surface ◽  
Carbon Flux ◽  
Meteorological Data ◽  
Aerodynamic Resistance ◽  
Mean Annual Precipitation ◽  
Leaf Wetness ◽  
Rainfall Events ◽  
Vapor Flux ◽  
Mountainous Regions

Abstract. This study compares the performance of the Community Land Models (CLM4.5 and CLM5) against tower and ground measurements from a tropical montane rainforest in Costa Rica. The study site receives over 4,000 mm of mean annual precipitation and has high daily levels of relative humidity. The measurement tower is equipped with eddy-covariance and vertical profile systems able to measure various micrometeorological variables, particularly in wet and complex terrain. In this work, results from point-scale simulation for both CLM4.5 and its updated version (CLM5) are compared to observed canopy flux and micro-meteorological data. Both models failed to capture the effects of frequent rainfall events and mountainous topography on the variables of interest (temperatures, leaf wetness, and fluxes). Overall, CLM5 alleviates some errors in CLM4.5 but CLM5 still cannot precisely simulate a number of canopy processes for this forest. Soil, air, and canopy temperatures, as well as leaf wetness, remain too sensitive to incoming solar radiation rates despite updates to the model. As a result, daytime vapor flux and carbon flux are overestimated, and modeled temperature differences between day and night are higher than those observed. Slope effects appear in the measured average diurnal variations of surface albedo and carbon flux, but CLM5 cannot simulate these features. This study suggests that both CLM models still require further improvements concerning energy partitioning processes, such as leaf wetness process, photosynthesis model, and aerodynamic resistance model for wet and mountainous regions.

scholarly journals An LSWI-Based Method for Mapping Irrigated Areas in China Using Moderate-Resolution Satellite Data

2020 ◽  
Vol 12 (24) ◽  
pp. 4181
Author(s):  
Kunlun Xiang ◽  
Wenping Yuan ◽  
Liwen Wang ◽  
Yujiao Deng
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Statistical Data ◽  
Spatial Information ◽  
Hydrological Cycle ◽  
Mainland China ◽  
Mean Annual Precipitation ◽  
Irrigated Area ◽  
Moderate Resolution

Accurate spatial information about irrigation is crucial to a variety of applications, such as water resources management, water exchange between the land surface and atmosphere, climate change, hydrological cycle, food security, and agricultural planning. Our study proposes a new method for extracting cropland irrigation information using statistical data, mean annual precipitation and Moderate Resolution Imaging Spectroradiometer (MODIS) land cover type data and surface reflectance data. The approach is based on comparing the land surface water index (LSWI) of cropland pixels to that of adjacent forest pixels with similar normalized difference vegetation index (NDVI). In our study, we validated the approach over mainland China with 612 reference samples (231 irrigated and 381 non-irrigated) and found the accuracy of 62.09%. Validation with statistical data also showed that our method explained 86.67 and 58.87% of the spatial variation in irrigated area at the provincial and prefecture levels, respectively. We further compared our new map to existing datasets of FAO/UF, IWMI, Zhu and statistical data, and found a good agreement with the irrigated area distribution from Zhu’s dataset. Results show that our method is an effective method apply to mapping irrigated regions and monitoring their yearly changes. Because the method does not depend on training samples, it can be easily repeated to other regions.

scholarly journals Assessment of Near-Real-Time Satellite Precipitation Products from GSMaP in Monitoring Rainfall Variations over Taiwan

2021 ◽  
Vol 13 (2) ◽  
pp. 202
Author(s):  
Wan-Ru Huang ◽  
Pin-Yi Liu ◽  
Jie Hsu ◽  
Xiuzhen Li ◽  
Liping Deng
Keyword(s):  
Real Time ◽  
Complex Terrain ◽  
Daily Rainfall ◽  
Rainfall Estimation ◽  
Rainfall Events ◽  
Satellite Precipitation ◽  
Different Seasons ◽  
Daily Scale ◽  
Rainfall Variations ◽  
Southwestern Taiwan

This study assessed four near-real-time satellite precipitation products (NRT SPPs) of Global Satellite Mapping of Precipitation (GSMaP)—NRT v6 (hereafter NRT6), NRT v7 (hereafter NRT7), Gauge-NRT v6 (hereafter GNRT6), and Gauge-NRT v7 (hereafter GNRT7)— in representing the daily and monthly rainfall variations over Taiwan, an island with complex terrain. The GNRT products are the gauge-adjusted version of NRT products. Evaluations for warm (May–October) and cold months (November–April) were conducted from May 2017 to April 2020. By using observations from more than 400 surface gauges in Taiwan as a reference, our evaluations showed that GNRT products had a greater error than NRT products in underestimating the monthly mean rainfall, especially during the warm months. Among SPPs, NRT7 performed best in quantitative monthly mean rainfall estimation; however, when examining the daily scale, GNRT6 and GNRT7 were superior, particularly for monitoring stronger (i.e., more intense) rainfall events during warm and cold months, respectively. Spatially, the major improvement from NRT6 to GNRT6 (from NRT7 to GNRT7) in monitoring stronger rainfall events over southwestern Taiwan was revealed during warm (cold) months. From NRT6 to NRT7, the improvement in daily rainfall estimation primarily occurred over southwestern and northwestern Taiwan during the warm and cold months, respectively. Possible explanations for the differences between the ability of SPPs are attributed to the algorithms used in SPPs. These findings highlight that different NRT SPPs of GSMaP should be used for studying or monitoring the rainfall variations over Taiwan for different purposes (e.g., warning of floods in different seasons, studying monthly or daily precipitation features in different seasons, etc.).

scholarly journals Subgrid snow depth coefficient of variation spanning alpine to sub-alpine mountainous terrain

2021 ◽  
Author(s):  
Graham A. Sexstone ◽  
Steven R. Fassnacht ◽  
Juan I. López-Moreno ◽  
Christopher A. Hiemstra
Keyword(s):  
Coefficient Of Variation ◽  
Land Surface ◽  
Snow Depth ◽  
Mountainous Terrain ◽  
Mountainous Regions ◽  
Scale Modeling ◽  
Roughness Elements ◽  
Wide Range ◽  
Performance Statistics ◽  
Snowpack Properties

Given the substantial variability of snow in complex mountainous terrain, a considerable challenge of coarse scale modeling applications is accurately representing the subgrid variability of snowpack properties. The snow depth coefficient of variation (CVds) is a useful metric for characterizing subgrid snow distributions but has not been well defined by a parameterization for mountainous environments. This study utilizes lidar-derived snow depth datasets spanning alpine to sub-alpine mountainous terrain in Colorado, USA to evaluate the variability of subgrid snow distributions within a grid size comparable to a 1000 m resolution common for hydrologic and land surface models. The subgrid CVds exhibited a wide range of variability across the 321 km2 study area (0.15 to 2.74) and was significantly greater in alpine areas compared to subalpine areas. Mean snow depth was the dominant driver of CVds variability in both alpine and subalpine areas, as CVds decreased nonlinearly with increasing snow depths. This negative correlation is attributed to the static size of roughness elements (topography and canopy) that strongly influence seasonal snow variability. Subgrid CVds was also strongly related to topography and forest variables; important drivers of CVds included the subgrid variability of terrain exposure to wind in alpine areas and the mean and variability of forest metrics in subalpine areas. Two statistical models were developed (alpine and subalpine) for predicting subgrid CVds that show reasonable performance statistics. The methodology presented here can be used for characterizing the variability of CVds in snow-dominated mountainous regions, and highlights the utility of using lidar-derived snow datasets for improving model representations of snow processes.

scholarly journals Observations and  Modelling of Precipitation  in the Southern Alps of  New Zealand

2021 ◽  
Author(s):  
◽  
Stephen John Stuart
Keyword(s):  
New Zealand ◽  
Climate Model ◽  
Regional Climate ◽  
Rain Gauge ◽  
Southern Alps ◽  
Annual Rainfall ◽  
Mean Annual Precipitation ◽  
Mountain Range ◽  
Mountainous Regions ◽  
Orographic Rainfall

<p>Precipitation in the central Southern Alps affects glaciation, river flows and key economic activities, yet there is still uncertainty about its spatial distribution and primary influences. Long-term and future patterns of New Zealand precipitation can be estimated by the HadRM3P regional climate model (RCM) - developed by the United Kingdom Met Office - but orographic rainfall in the steep and rugged topography of the Southern Alps is difficult to simulate accurately at the 30-km resolution of the RCM. To quantify empirical relationships, observations of surface rainfall were gathered from rain gauges covering a broad region of the South Island. In four transects of the Hokitika, Franz Josef and Haast regions, the mean annual precipitation maxima of objectively interpolated profiles are consistently located 7-11 km southeast of the New Zealand Alpine Fault. The magnitude and shape of the rainfall profile across the Southern Alps are strongly influenced by the 850-hPa wind direction to the north of the mountain range, as determined by comparing rain-gauge observations to wind vectors from NCEP/NCAR Reanalysis 1. The observed profile of orographically enhanced rainfall was incorporated into a trivariate spline in order to interpolate precipitation simulated by the RCM. This downscaling method significantly improved the RCM's estimates of mean annual rainfall at stations in the Southern Alps region from 1971 to 2000, and RCM projections of future rainfall in mountainous regions may be similarly refined via this technique. The improved understanding of the observed rainfall distribution in the Southern Alps, as gained from this analysis, has a range of other hydrological applications and is already being used in 'downstream' modelling of glaciers.</p>

Mammals

Monteverde ◽  
2000 ◽  
Author(s):  
Robert M. Timm ◽  
Richard K. LaVal
Keyword(s):  
Costa Rica ◽  
Land Surface ◽  
Mammal Species ◽  
Human Disturbances ◽  
Habitat Changes ◽  
Mammal Fauna ◽  
Neotropical Mammals ◽  
Life Zone ◽  
Systematic Relationships ◽  
Diverse Groups

Costa Rica is one of the most biotically diverse countries on earth, with 4% of known terrestrial plant and animal species in only 0.04% of the world’s land surface. The country’s mammal fauna is equally diverse, with more than 207 species (4.8% of the world’s 4629 species) in an area of 51,022 km2. The majority of the world’s mammal species and Monteverde’s fauna are small (< 0.5 kg), nocturnal, and secretive. We know considerably less about most neotropical mammals and other vertebrates than we do about birds, which are more easily observed and communicate with sounds audible to humans. Although certain species of mammals have been studied in Costa Rica (Janzen 1983a, Timm 1994, Vaughan and Rodríguez 1994), and Monteverde is one of the best-known regions of the country biologically, there has been little work on the ecology, distribution, abundance, altitudinal zonation, systematic relationships, and biogeography of most mammals. Deforestation and other human disturbances have had a significant impact on the native mammals of the region; knowledge of Monteverde’s mammals is vital to understand how habitat changes affect tropical montane mammals. In this chapter, we provide an overview of the mammal fauna of the Monteverde area. We discuss the biology and abundance of some of the area’s species, document how these are changing, and explore conservation issues. Most of the research on mammals at Monteverde has centered on bats or rodents, the two most diverse groups. Much of our knowledge of other species consists of isolated observations. We augment published reports with unpublished observations made by ourselves and colleagues. We also examined most of the Monteverde mammal specimens in museum collections to verify species identifications and to understand better their systematics, ecology, and distribution. We integrate this information into a list of the mammals that occur in the region, document their occurrence in each life zone, and estimate their overall abundance.

scholarly journals The HadCM3 contribution to PlioMIP phase 2

2019 ◽  
Vol 15 (5) ◽  
pp. 1691-1713 ◽  
Author(s):  
Stephen J. Hunter ◽  
Alan M. Haywood ◽  
Aisling M. Dolan ◽  
Julia C. Tindall
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Deep Convection ◽  
Surface Air Temperature ◽  
Meridional Overturning Circulation ◽  
Mean Annual Precipitation ◽  
Phase 2 ◽  
The North ◽  
Orbital Configuration ◽  
Hadley Centre

Abstract. We present the UK's input into the Pliocene Model Intercomparison Project phase 2 (PlioMIP2) using the Hadley Centre Climate Model version 3 (HadCM3). The 400 ppm CO2 Pliocene experiment has a mean annual surface air temperature that is 2.9 ∘C warmer than the pre-industrial and a polar amplification of between 1.7 and 2.2 times the global mean warming. The Pliocene Research Interpretation and Synoptic Mapping (PRISM4) enhanced Pliocene palaeogeography accounts for a warming of 1.4 ∘C, whilst the CO2 increase from 280 to 400 ppm leads to a further 1.5 ∘C of warming. Climate sensitivity is 3.5 ∘C for the pre-industrial and 2.9 ∘C for the Pliocene. Precipitation change between the pre-industrial and Pliocene is complex, with geographic and land surface changes primarily modifying the geographical extent of mean annual precipitation. Sea ice fraction and areal extent are reduced during the Pliocene, particularly in the Southern Hemisphere, although they persist through summer in both hemispheres. The Pliocene palaeogeography drives a more intense Pacific and Atlantic meridional overturning circulation (AMOC). This intensification of AMOC is coincident with more widespread deep convection in the North Atlantic. We conclude by examining additional sensitivity experiments and confirm that the choice of total solar insolation (1361 vs. 1365 Wm−2) and orbital configuration (modern vs. 3.205 Ma) does not significantly influence the anomaly-type analysis in use by the Pliocene community.

scholarly journals Restoring mass conservation to shallow ice flow models over complex terrain

2013 ◽  
Vol 7 (1) ◽  
pp. 229-240 ◽  
Author(s):  
A. H. Jarosch ◽  
C. G. Schoof ◽  
F. S. Anslow
Keyword(s):  
Complex Terrain ◽  
Model Performance ◽  
Grid Cell ◽  
Mass Conservation ◽  
Ice Flow ◽  
Flow Models ◽  
Mountainous Regions ◽  
Steep Terrain ◽  
Flux Limiting ◽  
Ice Model

Abstract. Numerical simulation of glacier dynamics in mountainous regions using zero-order, shallow ice models is desirable for computational efficiency so as to allow broad coverage. However, these models present several difficulties when applied to complex terrain. One such problem arises where steep terrain can spuriously lead to large ice fluxes that remove more mass from a grid cell than it originally contains, leading to mass conservation being violated. This paper describes a vertically integrated, shallow ice model using a second-order flux-limiting spatial discretization scheme that enforces mass conservation. An exact solution to ice flow over a bedrock step is derived for a given mass balance forcing as a benchmark to evaluate the model performance in such a difficult setting. This benchmark should serve as a useful test for modellers interested in simulating glaciers over complex terrain.

scholarly journals Improving an Extreme Rainfall Detection System with GPM IMERG data

2019 ◽  
Vol 11 (6) ◽  
pp. 677 ◽  
Author(s):  
Paola Mazzoglio ◽  
Francesco Laio ◽  
Simone Balbo ◽  
Piero Boccardo ◽  
Franca Disabato
Keyword(s):  
Detection System ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
Mean Annual Precipitation ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Time Aggregation ◽  
Spatial Coverage ◽  
Rainfall Detection

Many studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: erds.ithacaweb.org). This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation.

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