Spatial and Temporal Variations in Indian Summer Monsoon Rainfall and Temperature: An Analysis Based on RegCM3 Simulations

Regional climate models are important tools to examine the spatial and temporal characteristics of rainfall and temperature at high resolutions. Such information has potential applications in sectors like agriculture and health. In this study, the Regional Climate Model Version 3 (RegCM3) has been integrated in the ensemble mode at 55 km resolution over India for the summer monsoon season during the years 1982–2009. Emphasis has been given on the validation of the model simulation at the regional level. In Central India, both rainfall and temperature show the best correlations with respective observed values. The model gives rise to large wet biases over Northwest and Peninsular India. RegCM3 slightly underestimates the summer monsoon precipitation over the Central and Northeast India. Nevertheless, over these regions, RegCM3 simulated rainfall is closer to the observations when compared to the other regions where rainfall is overestimated. The position of the monsoon trough simulated by the model lies to the north of its original observed position. This is similar to the usual monsoon break conditions leading to less rainfall over Central India. RegCM3 simulated surface maximum temperature shows a large negative bias over the country while the surface minimum temperature is close to the observation. Nevertheless, there is a strong correlation between the all India weighted average surface temperature simulated by RegCM3 and IMD observed values. While examining the extreme weather conditions in Central India, it is found that RegCM3 simulated frequencies of occurrence of very wet days, extremely wet days, warm days and warm nights more often as compared to those in IMD observed values. However, these are systematic biases. The model biases in the frequencies of distribution of rainfall extremes explain the wet and dry biases in different regions in the country. Overall, the inter-annual characteristics of both the rainfall and temperature extremes simulated by RegCM3 in Central India are well in phase with those found in the observed data.     

A Study of Mean Winter Circulation Characteristics and Energetics over Southeastern Asia

A mean climatology is studied to examine atmospheric circulation characteristics to assess the wintertime (December, January, February and March - DJFM) synoptic weather system affecting northern India. The main objective is to study the mean circulation and mean energetics distribution pertaining to the winter season, which are embedded with an eastward moving synoptic weather system in westerlies, called Western Disturbances (WDs). Forty years (1958–1997) of uninitialized daily re-analysis data of the National Center for Environmental Prediction - National Center for Atmospheric Research (NCEP- NCAR, henceafter NCEP), U.S. has been considered for this study. Winter circulations are considered over the domain 15°S–45°N and 30°E–120°E. This domain is considered particularly to illustrate the impact of wintertime synoptic weather system Western Disturbances (WDs), which travel towards the east over the western Himalayas during winter and yield an enormous amount of precipitation in the form of snow. Large-scale balances of kinetic energy, vorticity, angular momentum, heat and moisture budget terms are analyzed. The main findings of the study show that strong rising motion in the extratropical region brings a significant amount of precipitation over the region of study. Also, horizontal flux of kinetic energy converges in the tropical region and diverges over the extratropical region. It is seen that both the zonal and meridional component of kinetic energy contributes to the production of kinetic energy in the upper troposphere. Vorticity budget shows that wintertime circulation over the western Himalayas is characterized by a negative generation of vorticity. The relative and planetary vorticity advection contributes to the horizontal transport of vorticity. The moisture flux transported into the region shows that in the middle tropospheric levels moisture undergoes phase transformation due to turbulent exchange and hence releases latent heat.     

Role of the Himalayan Orography in Simulation of the Indian Summer Monsoon using RegCM3

In this study, sensitivity of the Indian summer monsoon simulation to the Himalayan orography representation in a regional climate model (RegCM) is examined. The prescribed height of the Himalayan orography is less in the RegCM model than the actual height of the Himalayas. Therefore, in order to understand the impact of the Himalayan orography representation on the Indian summer monsoon, the height of the Himalayan orography is increased (decreased) by 10 % from its control height in the RegCM model. Three distinct monsoon years such as deficit (1987), excess (1988) and normal rainfall years are considered for this study. The performance of the RegCM model is tested with the use of a driving force from the reanalysis data and a global model output. IMD gridded rainfall and the reanalysis-2 data are used as verification analysis to validate the model results. The RegCM model has the potential to represent mean rainfall distribution over India as well as the upper air circulation patterns and some of the semi-permanent features during the Indian summer monsoon season. The skill of RegCM is reasonable in representing the variation in circulation and precipitation pattern and intensity during two contrasting rainfall years. The simulated seasonal mean rainfall over many parts of India especially, the foothills of the Himalaya, west coast of India and over the north east India along with the whole of India are more when the orography height is increased. The low level southwesterly wind including the Somali jet stream as well as upper air circulation associated with the tropical easterly jet stream become stronger with the enhancement of the Himalayan orography. Statistical analysis suggests that the distribution and intensity of rainfall is represented better with the increased orography of RegCM by 10 % from its control height. Thus, representation of the Himalayan orography in the model is close to actual and may enhance the skill in seasonal scale simulation of the Indian summer monsoon.     

Weather observations on Whistler Mountain during five storms

A greater understanding of precipitation formation processes over complex terrain near the west coast of British Colombia will contribute to many relevant applications, such as climate studies, local hydrology, transportation, and winter sport competition. The phase of precipitation is difficult to determine because of the warm and moist weather conditions experienced during the wintertime in coastal mountain ranges. The goal of this study is to investigate the wide range of meteorological conditions that generated precipitation on Whistler Mountain from 4–12 March 2010 during the SNOW-V10 field campaign. During this time period, five different storms were documented in detail and were associated with noticeably different meteorological conditions in the vicinity of Whistler Mountain. New measurement techniques, along with the SNOW-V10 instrumentation, were used to obtain in situ observations during precipitation events along the Whistler mountainside. The results demonstrate a high variability of weather conditions ranging from the synoptic-scale to the macro-scale. These weather events were associated with a variation of precipitation along the mountainside, such as events associated with snow, snow pellets, and rain. Only two events associated with a rain–snow transition along the mountainside were observed, even though above-freezing temperatures along the mountainside were recorded 90 % of the time. On a smaller scale, these events were also associated with a high variability of snowflake types that were observed simultaneously near the top of Whistler Mountain. Overall, these detailed observations demonstrate the importance of understanding small-scale processes to improve observational techniques, short-term weather prediction, and longer-term climate projections over mountainous regions.     

区域气候模式RegCM3对华北地区未来气候变化的数值模拟

采用高水平分辨率区域气候模式进行区域未来气候变化预估,对理解全球增暖对区域气候的潜在影响和科学评估区域气候变化有很好的参考价值.这里对国家气候中心使用25 km高水平分辨率区域气候模式RegCM3单向嵌套全球模式MIROC3.2_hires在观测温室气体(1951—2000)和IPCC A1B温室气体排放情景下(2001—2100)进行的共计150年长时间模拟结果,进行华北地区未来气温、降水和极端气候事件变化的分析.模式检验结果表明:模式对当代(1981—2000)气温以及和气温有关的极端气候事件(霜冻日数、生长季长度)的空间分布和数值模拟较好;对降水及和降水有关的极端气候事件(强降水日期、降水强度、五日最大降水量)能够模拟出它们各自的主要空间分布特征,但在模拟数值上存在偏大、偏强的误差.和全球模式驱动场相比,区域模式模拟的气温、降水和极端气候事件有明显的改进.2010—2100年华北地区随时间区域平均气温升高幅度逐渐增大,随之霜冻日数逐渐减少,生长季长度逐渐增多;同时随温室效应的不断加剧,未来降水呈增加的趋势,强降水日期和五日最大降水量逐渐增多、降水强度逐渐增大.从空间分布看,21世纪末期(2081—2100)气温、降水以及有关的极端气候事件变化比21世纪中期(2041—2060)更加明显.     

Land use effects on climate in China as simulated by a regional climate model

A regional climate model (RegCM3) nested within ERA40 re-analyzed data is used to investigate the climate effects of land use change over China. Two 15-year simulations (1987―2001), one with current land use and the other with potential vegetation cover without human intervention, are conducted for a domain encompassing China. The climate impacts of land use change are assessed from the difference between the two simulations. Results show that the current land use (modified by anthropogenic ac- tivities) influences local climate as simulated by the model through the reinforcement of the monsoon circulation in both the winter and summer seasons and through changes of the surface energy budget. In winter, land use change leads to reduced precipitation and decreased surface air temperature south of the Yangtze River, and increased precipitation north of the Yangtze River. Land use change signifi- cantly affects summer climate in southern China, yielding increased precipitation over the region, de- creased temperature along the Yangtze River and increased temperature in the South China area (south-end of China). In summer, a reduction of precipitation over northern China and a temperature rise over Northwest China are also simulated. Both daily maximum and minimum temperatures are affected in the simulations. In general, the current land use in China leads to enhanced mean annual precipitation and decreased annual temperature over south China along with decreased precipitation over North China.     

Improvement of snowpack simulations in a regional climate model

To improve simulations of regional‐scale snow processes and related cold‐season hydroclimate, the Community Land Model version 3 (CLM3), developed by the National Center for Atmospheric Research (NCAR), was coupled with the Pennsylvania State University/NCAR fifth‐generation Mesoscale Model (MM5). CLM3 physically describes the mass and heat transfer within the snowpack using five snow layers that include liquid water and solid ice. The coupled MM5–CLM3 model performance was evaluated for the snowmelt season in the Columbia River Basin in the Pacific Northwestern United States using gridded temperature and precipitation observations, along with station observations. The results from MM5–CLM3 show a significant improvement in the SWE simulation, which has been underestimated in the original version of MM5 coupled with the Noah land‐surface model. One important cause for the underestimated SWE in Noah is its unrealistic land‐surface structure configuration where vegetation, snow and the topsoil layer are blended when snow is present. This study demonstrates the importance of the sheltering effects of the forest canopy on snow surface energy budgets, which is included in CLM3. Such effects are further seen in the simulations of surface air temperature and precipitation in regional weather and climate models such as MM5. In addition, the snow‐season surface albedo overestimated by MM5–Noah is now more accurately predicted by MM5–CLM3 using a more realistic albedo algorithm that intensifies the solar radiation absorption on the land surface, reducing the strong near‐surface cold bias in MM5–Noah. The cold bias is further alleviated due to a slower snowmelt rate in MM5–CLM3 during the early snowmelt stage, which is closer to observations than the comparable components of MM5–Noah. In addition, the over‐predicted precipitation in the Pacific Northwest as shown in MM5–Noah is significantly decreased in MM5–CLM3 due to the lower evaporation resulting from the longer snow duration. Copyright © 2011 John Wiley & Sons, Ltd.     

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Understanding climate change impacts on hydrological regime and assessing future water supplies are essential to effective water resources management and planning, which is particularly true for the Tibetan Plateau (TP), one of the most vulnerable areas to climate change. In this study, future climate change in the TP was projected for 2041–2060 by a high‐resolution regional climate model, RegCM4, under 3 representative concentration pathways (RCPs): 2.6, 4.5, and 8.5. Response of all key hydrological elements, that is, evapotranspiration, surface run‐off, baseflow, and snowmelt, to future climate in 2 typical catchments, the source regions of Yellow and Yangtze rivers, was further investigated by the variable infiltration capacity microscale hydrological model incorporated with a 2‐layer energy balance snow model and a frozen soil/permafrost algorithm at a 0.25°×0.25° spatial scale. The results reveal that (a) spatial patterns of precipitation and temperature from RegCM4 agree fairly well with the data from China Meteorological Forcing Dataset, indicating that RegCM4 well reproduces historical climatic information and thus is reliable to support future projection; (b) precipitation increase by 0–70% and temperature rise by 1–4 °C would occur in the TP under 3 RCPs. A clear south‐eastern–north‐western spatial increasing gradient in precipitation would be seen. Besides, under RCP8.5, the peak increase in temperature would approach to 4 °C in spring and autumn in the east of the TP; (c) evapotranspiration would increase by 10–60% in 2 source regions due to the temperature rise, surface run‐off and baseflow in higher elevation region would experience larger increase dominantly due to the precipitation increase, and streamflow would display general increases by more than 3% and 5% in the source regions of Yellow and Yangtze rivers, respectively; (d) snowmelt contributes 11.1% and 16.2% to total run‐off in the source regions of Yellow and Yangtze rivers, respectively, during the baseline period. In the source region of Yangtze River, snowmelt run‐off would become more important with increase of 17.5% and 18.3%, respectively, under RCP2.6 and RCP4.5 but decrease of 15.0% under RCP8.5.     

Estimating the effects of climate change on the intensification of monsoonal‐driven stream discharge in a Himalayan watershed

Understanding potential hydrologic influences to continued climate change in Himalayan watersheds is important for management of transnational water resources. This study estimates the climate change impacts on hydrologic processes of the Kali Gandaki watershed from central Himalayan region using the Soil and Water Assessment Tool. Daily predicted stream discharge of the basin for 1981–95 following calibration was accurate with Nash Sutcliffe Efficiency value >0.75. Sensitivity analysis of the hydrologic parameters showed the precipitation and temperature lapse rates as the most sensitive parameters to the stream discharge. To assess the influence of continued climate change on hydrologic processes, we modified the weather inputs for the model using average, minimum and maximum temperature, and precipitation changes for the Special Report on Emission Scenarios B1, A1B and A2 derived from 16 General Circulation Models for 2080s. Mean annual stream discharge was approximately 39% higher than current values for the maximum temperature and precipitation changes of the A2 scenario and 22% less for minimum changes of the same scenario. Stream discharge was projected to be changed by +9% during monsoon season and by ?6% during pre‐monsoon season. Snowfall and snow melt were projected to be 30% and 29%, respectively, less than the current average for the maximum temperature and precipitation changes of the A2 scenario. Future simulations showed potential increase in monsoonal stream discharge associated with projected higher precipitation which when coupled with enhanced summer glacier melt might influence the downstream water availability of the basin. Copyright © 2013 John Wiley & Sons, Ltd.     

用全球大气环流模式嵌套区域气候模式模拟东亚现代气候

将区域气候模式RegCM2与中国科学院大气物理研究所的9层全球格点大气环流模式IAP AGCM单向嵌套,对东亚现代气候进行数值模拟研究,同时检验和分析该嵌套模式的性能.已完成的10年积分结果表明,单向嵌套RegCM2由于具有较高分辨率和较完善的物理过程,因此对地面气温和降水的空间分布形势和季节变化趋势都有较好的模拟能力,且较与之嵌套的IAP AGCM的模拟效果有较大改善,如在中国区域,它模拟的年均地面气温与实况的空间相关系数由全球环流模式的092提高到094,模拟的年均降水由05提高到07. 这与嵌套RegCM2能模拟出IAP AGCM所不能分辨的中尺度信号有很大关系.     

A Downscaling Approach Toward High-Resolution Surface Mass Balance Over Antarctica

The Antarctic ice sheet surface mass balance shows high spatial variability over the coastal area. As state-of-the-art climate models usually require coarse resolutions to keep computational costs to a moderate level, they miss some local features that can be captured by field measurements. The downscaling approach adopted here consists of using a cascade of atmospheric models from large scale to meso-?? scale. A regional climate model (Modèle Atmosphérique Régional) forced by meteorological reanalyses provides a diagnostic physically-based rain- and snowfall downscaling model with meteorological fields at the regional scale. Although the parameterizations invoked by the downscaling model are fairly simple, the knowledge of small-scale topography significantly improves the representation of spatial variability of precipitation and therefore that of the surface mass balance. Model evaluation is carried out with the help of shallow firn cores and snow height measurements provided by automatic weather stations. Although downscaling of blowing snow still needs to be implemented in the model, the net accumulation gradient across Law Dome summit is shown to be induced mostly by orographic effects on precipitation.     

Response of snow processes to climate change: spatial variability in a small basin in the Spanish Pyrenees

In this study, the Cold Regions Hydrological Modelling platform was used to create an alpine snow model including wind redistribution of snow and energy balance snowmelt to simulate the snowpack over the period 1996–2009 in a small (33 ha) snow‐dominated basin in the Spanish Pyrenees. The basin was divided into three hydrological response units (HRUs), based on contrasting physiographic and aerodynamic characteristics. A sensitivity analysis was conducted to calculate the snow water equivalent regime for various combinations of temperature and precipitation that differed from observed conditions. The results show that there was large inter‐annual variability in the snowpack in this region of the Pyrenees because of its marked sensitivity to climatic conditions. Although the basin is small and quite homogeneous, snowpack seasonality and inter‐annual evolution of the snowpack varied in each HRU. Snow accumulation change in relation to temperature change was approximately 20% for every 1 °C, and the duration of the snowpack was reduced by 20–30 days per °C. Melting rates decreased with increased temperature, and wind redistribution of snow was higher with decreased temperature. The magnitude and sign of changes in precipitation may markedly affect the response of the snowpack to changes in temperature. There was a non‐linear response of snow to individual and combined changes in temperature and precipitation, with respect to both the magnitude and sign of the change. This was a consequence of the complex interactions among climate, topography and blowing snow in the study basin. Copyright © 2012 John Wiley & Sons, Ltd.     

Increasing water losses from snow captured in the canopy of boreal forests: A case study using a 30 year data set

Water losses from snow intercepted by forest canopy can significantly influence the hydrological cycle in seasonally snow‐covered regions, yet how snow interception losses (SIL) are influenced by a changing climate are poorly understood. In this study, we used a unique 30 year record (1986–2015) of snow accumulation and snow water equivalent measurements in a mature mixed coniferous (Picea abies and Pinus sylvestris ) forest stand and an adjacent open area to assess how changes in weather conditions influence SIL. Given little change in canopy cover during this study, the 20% increase in SIL was likely the result of changes in winter weather conditions. However, there was no significant change in average wintertime precipitation and temperature during the study period. Instead, mean monthly temperature values increased during the early winter months (i.e., November and December), whereas there was a significant decrease in precipitation in March. We also assessed how daily variation in meteorological variables influenced SIL and found that about 50% of the variation in SIL was correlated to the amount of precipitation that occurred when temperatures were lower than ?3 °C and to the proportion of days with mean daily temperatures higher than +0.4 °C. Taken together, this study highlights the importance of understanding the appropriate time scale and thresholds in which weather conditions influence SIL in order to better predict how projected climate change will influence snow accumulation and hydrology in boreal forests in the future.     

Quantifying groundwater sensitivity and resilience over peninsular India

Groundwater in India plays an important role to support livelihoods and maintain ecosystems and the present rate of depletion of groundwater resources poses a serious threat to water security. Yet, the sensitivity of the hydrological processes governing groundwater recharge to climate variability remains unclear in the region. Here we assess the groundwater sensitivity (precipitation–recharge relationship) and its potential resilience towards climatic variability over peninsular India using a conceptual water balance model and a convex model, respectively in 54 catchments over peninsular India. Based on the model performance using a comprehensive approach (Nash Sutcliffe Efficiency [NSE], bias and variability), 24 out of 54 catchments are selected for assessment of groundwater sensitivity and its resilience. Further, a systematic approach is used to understand the changes in resilience on a temporal scale based upon the convex model and principle of critical slowing down theory. The results of the study indicate that the catchments with higher mean groundwater sensitivity (GWS) encompass high variability in GWS over the period (1988–2011), thus indicating the associated vulnerability towards hydroclimatic disturbances. Moreover, it was found that the catchments pertaining to a lower magnitude of mean resilience index incorporates a high variability in resilience index over the period (1993–2007), clearly illustrating the inherent vulnerability of these catchments. The resilience of groundwater towards climatic variability and hydroclimatic disturbances that is revealed by groundwater sensitivity is essential to understand the future impacts of changing climate on groundwater and can further facilitate effective adaptation strategies.     

The vertical influence of temperature and precipitation on snow cover variability in the Central Tianshan Mountains,Northwest China

Seasonal snow cover in mountainous regions will affect local climate and hydrology. In this study, we assessed the role of altitude in determining the relative importance of temperature and precipitation in snow cover variability in the Central Tianshan Mountains. The results show that: (a) in the study area, temperature has a greater influence on snow cover than precipitation during most of the time period studied and in most altitudes. (b) In the high elevation area, there is a threshold altitude of 3,900 ± 400 m, below which temperature is negatively correlated whereas precipitation is positively correlated to snow cover, and above which the situation is the opposite. Besides, this threshold altitude decreases from snow accumulated period to snow stable period and then increases from snowmelt period to snow‐free period. (c) Below 2,000 m, there is another threshold altitude of 1,400 ± 100 m during the snow stable period, below (above) which precipitation (temperature) is the main driver of snow cover.     

Isotopic analysis to quantify the role of the Indian monsoon on water resources of selected river basins in the Himalayas

Western disturbances (WDs) and Indian summer monsoon (ISM) led precipitation play a central role in the Himalayan water budget. Estimating their contributions to water resource is although a challenging but essential for hydrologic understanding and effective water resource management. In this study, we used stable water isotope data of precipitation and surface waters to estimate the contribution of ISM and WDs to the water resources in three mountainous river basins - Indus, Bhagirathi and Teesta river basins of western, central and Eastern Himalayas. The study reveals distinct seasonality in isotope characteristics of precipitation and surface waters in each river basin is due to changes in moisture source, hydrometeorology and relief. Despite steady spatial variance in the slope and intercept of regression lines from the Teesta to Indus and the Bhagirathi river basins, the slope and intercept are close to the global meteoric water line and reported local meteoric water line of other regions in the Himalayas and the Tibetan Plateau. The two-component end-member mixing method using d-excess as tracer were used to estimate the contribution from ISM and WD led precipitation to surface water in aforementioned river basins. The results suggest that the influence of the ISM on the water resources is high (>72% to annual river flow) in Teesta river basin (eastern Himalayas), while as the WDs led precipitation is dominantly contributing (>70% average annual river flow) to the surface waters in the Indus river basin (western Himalayas). The contribution of ISM and WD led precipitation in Bhagirathi river basin is 60% and 40%, respectively. The findings demonstrate that the unusual changes in the ISM and WD moisture dynamics have the potential to affect the economy and food security of the region, which is dependent on the availability of water resources. The obtained results are of assistance to policy makers/mangers to make use of the information for better understanding hydrologic response amid unusual behaviour of the dual monsoon system over the region.     

Spatio-temporal heterogeneity and changes in extreme precipitation over eastern Himalayan catchments India

This study draws attention on the extreme precipitation changes over the eastern Himalayan region of the Teesta river catchment. To explore the precipitation variability and heterogeneity, observed (1979–2005) and statistically downscaled (2006–2100) Coupled Model Intercomparison Project Phase Five earth system model global circulation model daily precipitation datasets are used. The trend analysis is performed to analyze the long-term changes in precipitation scenarios utilizing non-parametric Mann–Kendall (MK) test, Kendall Tau test, and Sen’s slope estimation. A quantile regression (QR) method has been applied to assess the lower and upper tails changes in precipitation scenarios. Precipitation extreme indices were generated to quantify the extremity of precipitation in observed and projected time domains. To portrait the spatial heterogeneity, the standard deviation and skewness are computed for precipitation extreme indices. The results show that the overall precipitation amount will be increased in the future over the Himalayan region. The monthly time series trend analysis based results reflect an interannual variability in precipitation. The QR analysis results showed significant increments in precipitation amount in the upper and lower quantiles. The extreme precipitation events are increased during October to June months; whereas, it decreases from July to September months. The representative concentration pathway (RCP) 8.5 based experiments showed extreme changes in precipitation compared to RCP2.6 and RCP4.5. The precipitation extreme indices results reveal that the intensity of precipitation events will be enhanced in future time. The spatial standard deviation and skewness based observations showed a significant variability in precipitation over the selected Himalayan catchment.     

OBSERVATIONS ON THE HINTEREIS AND VERNAGTFERNER

Abstract

Adequate water resources management at the basin level needs quality downscaling of climate change scenarios for application to impact assessment and adaptation work. This study evaluates the ability of a regional climate model (RegCM3) to simulate the present-day climate and regional water balance over the Niger River Basin (NRB). RegCM3 gives a good simulation of the NRB hydroclimatic features. The mean bias error for monthly temperature is 1.5°C, 0.3 mm d^-1 for rainfall, and 0.4 mm d^-1 for runoff. Moderate to high correlations (0.66–0.95) were found between the modelled and the observed variables. RegCM3-based water cycling indices were not statistically different from the observation. Seasonal moistening efficiency (m) ranges between 19% and 37%; 66% of the available atmospheric moisture over NRB precipitates between June and September, of which 21% originates from local evaporation. The result suggests that the moisture sink period is July to October with very high precipitation efficiency over the basin. The model reproduces the hydroclimatology of the NRB and hence is a suitable tool for further studies relating to the assessment of climate change impacts on river basin water systems.

Editor Z. W. Kundzewicz; Associate editor D. Hughes     

Simulating precipitation in the Northeast United States using a climate-informed K-nearest neighbour algorithm

Decadal prediction using climate models faces long-standing challenges. While global climate models may reproduce long-term shifts in climate due to external forcing, in the near term, they often fail to accurately simulate interannual climate variability, as well as seasonal variability, wet and dry spells, and persistence, which are essential for water resources management. We developed a new climate-informed K-nearest neighbour (K-NN)-based stochastic modelling approach to capture the long-term trend and variability while replicating intra-annual statistics. The climate-informed K-NN stochastic model utilizes historical data along with climate state information to provide improved simulations of weather for near-term regional projections. Daily precipitation and temperature simulations are based on analogue weather days that belong to years similar to the current year's climate state. The climate-informed K-NN stochastic model is tested using 53 weather stations in the Northeast United States with an evident monotonic trend in annual precipitation. The model is also compared to the original K-NN weather generator and ISIMIP-2b GFDL general circulation model bias-corrected output in a cross-validation mode. Results indicate that the climate-informed K-NN model provides improved simulations for dry and wet regimes, and better uncertainty bounds for annual average precipitation. The model also replicates the within-year rainfall statistics. For the 1961–1970 dry regime, the model captures annual average precipitation and the intra-annual coefficient of variation. For the 2005–2014 wet regime, the model replicates the monotonic trend and daily persistence in precipitation. These improved modelled precipitation time series can be used for accurately simulating near-term streamflow, which in turn can be used for short-term water resources planning and management.     

Evaluation of snow water equivalent datasets over the Saint‐Maurice river basin region of southern Québec

A 10‐km gridded snow water equivalent (SWE) dataset is developed over the Saint‐Maurice River basin region in southern Québec from kriging of observed snow survey data for evaluation of SWE products. The gridded SWE dataset covers 1980–2014 and is based on manual gravimetric snow surveys carried out on February 1, March 1, March 15, April 1, and April 15 of each snow season, which captures the annual maximum SWE (SWEM) with a mean interpolation error of ±19%. The dataset is used to evaluate SWEM from a range of sources including satellite retrievals, reanalyses, Canadian regional climate models, and the Canadian Meteorological Centre operational snow depth analysis. We also evaluate a number of solid precipitation datasets to determine their contribution to systematic errors in estimated SWEM. None of the evaluated datasets is able to provide estimates of SWEM that are within operational requirements of ±15% error, and insufficient solid precipitation is determined to be one of the main reasons. The Climate System Forecast Reanalysis is the only dataset where snowfall is sufficiently large to generate SWEM values comparable to observations. Inconsistencies in precipitation are also found to have a strong impact on year‐to‐year variability in SWEM dataset performance and spread. Version 3.6.1 of the Canadian Land Surface Scheme land surface scheme driven with ERA‐Interim output downscaled by Version 5.0.1 of the Canadian Regional Climate Model was the best physically based model at explaining the observed spatial and temporal variability in SWEM (root‐mean‐square error [RMSE] = 33%) and has potential for lower error with adjusted precipitation. Operational snow products relying on the real‐time snow depth observing network performed poorly due to a lack of real‐time data and the strong local scale variability of point snow depth observations. The results underscore the need for more effort to be invested in improving solid precipitation estimates for use in snow hydrology applications.