Analysis of rainfall characteristics of the Madden–Julian oscillation using TRMM satellite data

Rainfall characteristics of the Madden–Julian oscillation (MJO) are analyzed primarily using tropical rainfall measuring mission (TRMM) precipitation radar (PR), TRMM microwave imager (TMI) and lighting imaging sensor (LIS) data. Latent heating structure is also examined using latent heating data estimated with the spectral latent heating (SLH) algorithm.The zonal structure, time evolution, and characteristic stages of the MJO precipitation system are described. Stratiform rain fraction increases with the cloud activity, and the amplitude of stratiform rain variation associated with the MJO is larger than that of convective rain by a factor of 1.7. Maximum peaks of both convective rain and stratiform rain precede the minimum peak of the outgoing longwave radiation (OLR) anomaly which is often used as a proxy for the MJO convection. Stratiform rain remains longer than convective rain until ∼4000 km behind the peak of the mature phase. The stratiform rain contribution results in the top-heavy heating profile of the MJO.Associated with the MJO, there are tri-pole convective rain top heights (RTH) at 10–11, ∼7 and ∼3 km, corresponding to the dominance of afternoon showers, organized systems, and shallow convections, respectively. The stratiform rain is basically organized with convective rain, having similar but slightly lower RTH and slightly lags the convective rain maximum. It is notable that relatively moderate (∼7 km) RTH is dominant in the mature phase of the MJO, while very tall rainfall with RTH over 10 km and lightning frequency increase in the suppressed phase. The rain-yield-per flash (RPF) varies about 20–100% of the mean value of ∼2–10 × 10⁹ kg fl⁻¹ over the tropical warm ocean and that of ∼2–5 × 10⁹ kg fl⁻¹ over the equatorial Islands, between the convectively suppressed phase and the active phase of MJO, in the manner that RPF is smaller in the suppressed phase and larger in the active phase.     

Assimilation of satellite altimeter data in a primitive-equation model of the Azores–Madeira region

The aim of this study is to implement satellite altimetric assimilation into a high-resolution primitive-equation ocean model and check the validity and sensitivity of the results. Beyond this paper, the remote objective is to get a dynamical tool capable of simulating the surface ocean processes linked to the air–sea interactions as well as to perform mesoscale ocean forecasting. For computational cost and practical reasons, this study takes place in a 1000 by 1000 sq km open domain of the Canary basin. The assimilation experiments are carried out with the combined TOPEX/POSEIDON and ERS-1 data sets between June 1993 and December 1993. The space–time domain overlaps with in situ data collected during the SEMAPHORE experiment and thus enables an objective validation of the results. A special boundary treatment is applied to the model by creating a surrounding recirculating area separated from the interior by a buffer zone. The altimetric assimilation is done by implementing a reduced-order optimal interpolation algorithm with a special vertical projection of the surface model/data misfits. We perform a first experiment with a vertical projection onto an isopycnal EOF representing the Azores Current vertical variability. An objective validation of the model's velocities with Lagrangian float data shows good results (the correlation is 0.715 at 150 dbar). The question of the sensitivity to the vertical projection is addressed by performing similar experiments using a method for lifting/lowering of the water column, and using an EOF in Z-coordinates. Some comparisons with in situ temperature data do not show any significant difference between the three projections, after five months of assimilation. However, in order to preserve the large-scale water characteristics, we felt that the isopycnal projection was a more physically consistent choice. Then, the complementary character of the two satellites is assessed with two additional experiments which use each altimeter data sets separately. There is an evidence of the benefit of combining the two data sets. Otherwise, an experiment assimilating long-wavelength bias-corrected CLS altimetric maps every 10 days exhibits the best correlation scores and emphasizes the importance of reducing the orbit error and biases in the altimetric data sets. The surface layers of the model are forced using realistic daily wind stress values computed from ECMWF analyses. Although we resolve small space and time scales, in our limited domain the wind stress does not significantly influence the quality of the results obtained with the altimetric assimilation. Finally, the relative effects of the data selection procedure and of the integration times (cycle lengths) is explored by performing data window experiments. A value of 10 days seems to be the most satisfactory cycle length.     

Analysis of deep‐drogued satellite‐tracked drifter measurements in the northeast pacific

Abstract

We analyse the trajectories of 24 deep‐drogued, satellite‐tracked drifters launched between 50 and 52°N in the northeast Pacific during June and October 1987. Three aspects of the observed motions at the drogue depths of 100 to 120 m are studied: (i) the spatial structure of the mean and variance velocity fields; (ii) the dispersion and eddy diffusion characteristics of the fluctuating motions; and (iii) the properties of selected mesoscale eddies.

The mean Lagrangian velocity field is consistent with the mean flow pattern derived from the historical dynamic height topography. Fluctuating motions within the region are dominated by mesoscale eddies and meanders. Several instances of persistent O(100 days) westward flowing countercurrents were also observed. Based on the Lagrangian integral time‐ and length scales, drifter motions become decorrelated within a period of 10 days and a separation of 100 km. The mean zonal and meridional integral time‐scales of 4.5 and 3.6 days, respectively, are nearly identical with those obtained by Krauss and Böning (1987) from deep‐drogued drifter tracks in the North Atlantic. Because of the relatively small (<100 cm² s^?2) kinetic energy values in the northeast Pacific, the corresponding mean Lagrangian length scales of 29.4 and 29.9 km are roughly half those for the Atlantic.

The observed drifter dispersion is generally consistent with Taylor's (1921) theory for single‐particle dispersion in homogeneous isotropic turbulence. Estimates obtained using 476 pseudo‐drifter tracks generated from the original records indicate that the dispersion increases linearly with time, t, within the first 3 to 5 days of launch and subsequently increases as t^1/2 (the random‐walk regime) within 10 days of launch. The respective peak zonal and meridional eddy diffusion coefficients of 4.1 × and 3.8 × 10⁷ cm² s^?1 are reached within 30 days of deployment. Similar estimates for the peak eddy diffusivities are obtained using dispersion curves for sets of 4 drifters launched at the same location during the June and October deployments. The dispersion of these clusters followed an exponential rather than a t^1/2 dependence over the first 70 days after release.

Eddies are predominantly clockwise rotary and are characterized by radii of 26 ± 16 km, periods of rotation of 16.0 ± 5.2 days, and azimuthal current speeds of 12.7 ± 8.6 cm s^?1. One eddy was tracked for over 10 months. Oceanographic data collected during the October deployment period showed the eddies have vertical extents of 500 to 700 m and are linked to isotherm depressions of over 100 m in the main pycnocline. All eddies in the bifurcation zone propagate to the west at roughly 1.5 ± 0.4 cm s^?1 counter to the prevailing mean flow and winds. These speeds are consistent with the westward phase speeds of first mode baroclinic planetary (Rossby) waves.     

Improved estimation of average warming trend of China from 1951–2010 based on satellite observed land-use data

This paper provides new evidence of regional warming trends from local Chinese observations covering the period 1951–2010. We used satellite-derived land data and weighted urban and rural temperature records (a weighted method) and estimate the regional warming trend, which involves natural climate change and human impact. The annual warming rate over the whole of China is 0.21?±?0.02 °C/decade. The seasonal warming is 0.30?±?0.05 °C/decade (Winter), 0.24 °C?±?0.03 °C/decade (Spring); 0.16?±?0.02 °C/decade (Summer) and 0.21?±?0.03 °C/decade (Autumn). The mean warming trend is lower than previous estimates (e.g. NMIC, CRU-China) using un-weighted methods (arithmetic average of all records). The warming difference between the weighted and un-weighted accounts for 27 % (12 %) of the NMIC (CRU-China) un-weighted estimate on the total warming. This indicates that previous estimations overestimated a regional warming trend. The differences can be partly attributed to the weighting of the urban effect which is taken into consideration in this study, resulting in a much slower temperature increase. Spatially, the northern part of China shows a larger difference than the south especially for winter and spring. We argue that it is of importance to take into consideration the influence of urban land-use change to improve the physical understanding of surface warming in China over past decades.     

Global precipitation estimates from satellite: Using difference fields of outgoing long‐wave radiation

Abstract

Global precipitation estimates using satellite data are derived using difference fields of outgoing long‐wave radiation (OLR). The difference fields consist of clear OLR minus cloudy OLR, which is a measure of long‐wave cloud radiative forcing at the top of the earth‐atmosphere system; and clear daytime OLR minus clear night‐time OLR, which is a measure of the diurnal variation of surface heating. All geophysical parameters used to compute OLR are derived from an analysis of the HIRS2/MSU sounding data. The derived global precipitation estimates show good agreement with collocated raingauge data over land. The correlation coefficient between the precipitation estimates derived using difference fields of OLR and raingauge data over land is about 0.65 for the FGGEyear. The correlation coefficient between precipitation estimates derived using difference fields of OLR and the GOES Precipitation Index (GPI) fraction is about 0.914 from 30°S to 30°N for July 1983, and between the precipitation estimates derived using difference fields of OLR and the difference field of atmospheric reflectance is about 0.86.

Using one set of coefficients, global precipitation fields are derived for each 10‐day period and each month of the FGGE year (from December 1978 to November 1979). These fields contain rich information on seasonal variations.     

Spatial gridding of daily maximum and minimum 2 m temperatures supported by satellite observations

The usefulness of two remotely sensed variables, land surface temperature (LST) and cloud cover (CC), as predictors for the gridding of daily maximum and minimum 2 m temperature (T _min/T _max) was assessed. Four similar gridding methods were compared, each of which applied regression kriging to capture the spatial variation explained by the predictors used; however, both methods differed in the interpolation steps performed and predictor combinations used. The robustness of the gridding methods was tested for daily observations in January and July in the period 2009–2011 and in two different regions: the Central European region (CER) and the Iberian Peninsula (IP). Moreover, the uncertainty estimate provided by each method was evaluated using cross-validation. The regression analyses for both regions demonstrated the high predictive skills of LST for T _min and T _max on daily and monthly timescales (and lower predictive skills of CC). The application of LST as a predictor considerably improved the gridding performance over the IP region in July; however, there was only a slight improvement over the CER region. CC reduced the loss of spatial variability in the interpolated daily T _min/T _max values over the IP region. The interpolation skill was mainly controlled by the station density, but also depended on the complexity of the terrain. LST was shown to be of particular value for very low station densities (1 station per 50,000 km²). Analyses with artificially decreasing station densities showed that even in the case of very low station densities, LST allows the determination of useful regression functions.     

The delineation of rain areas from visible and IR satellite data for GATE and mid‐latitudes

Abstract

Two‐dimensional pattern matching has been used to delineate raining areas of clouds from GATE and Montreal GOES visible and IR satellite data, with radar as ground truth. For the cases examined, the cloud cover was of the order of 4 times larger than the rain area, requiring skill to separate out low‐thick or high‐thin non‐precipitating clouds from cumulus systems, which is difficult using a single threshold. The more flexible approach described here has allowed useful rain maps to be generated for all the types of weather systems examined. The optimum boundary separating raining from non‐raining areas is relatively insensitive to diurnal and day‐to‐day variations, but is different for the tropical Atlantic and for Montreal.     

How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman’s correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d^-1). A strong relationship between GPM rainfall and error was found from heavy (~35 mm d^-1) to violent rain (160 mm d^-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.     

Evaluation of solar irradiance at the surface—inferences from in situ and satellite observations and a mesoscale model

Accurate information about the solar irradiance at the soil surface is essential for many agricultural, hydrological and environmental models that take into account the surface energy balance. The main goal of present study was to evaluate the solar irradiance predictions from the Advanced Research Weather Research and Forecasting (ARW) model for both clear sky and cloudy conditions. An extended observational dataset from the Georgia Automated Environmental Monitoring Network (AEMN) provided hourly solar irradiance at the surface and other collocated surface level measurements. The radiation bias (determined from the difference between the ARW predictions and AEMN observations) showed a linear relationship with the cloud optical depth and the cirrus cloud amount from the moderate resolution imaging spectroradiometer (MODIS). For cloud-free days, the ARW model had a positive radiation bias that exceeded 120 W m^?2 over coastal and urban areas of Georgia. The model radiation and air temperature bias increased with increasing aerosol optical depth derived from the MODIS observations during the cloud-free days, attributed to fire events that lasted intermittently throughout the study period. The model biases of temperature, mixing ratio, wind speed, and soil moisture were linearly dependent on the radiation bias.     

A comparison of global tropospheric teleconnections using observed satellite and general circulation model total ozone column data for 1979–91

 The total ozone column is well correlated with tropospheric fields such as the heights of the upper tropospheric geopotential surfaces and thus it can provide useful information on temporal variability in the troposphere. The global availability of long period satellite measurements of the total ozone column, taken by the TOMS instruments since 1978, provides a valuable and independent data set for use in studies of seasonal and interannual climate variability. In this study, the global low-frequency seasonal teleconnections in the observed TOMS data from 1979–91 have been investigated using seasonal teleconnectivity maps and empirical orthogonal function analysis. They have also been compared with the results from a simulation made with the atmospheric GCM at Météo-France, having prescribed observed sea surface temperatures for the same period. In the observed total ozone, strong ENSO-related wave number one longitudinal dipole patterns are seen in both the tropics and in the Southern Hemisphere extratropics. The model shows much weaker variability in total ozone yet appears to be able to capture similar teleconnection patterns in the tropics related to ENSO. In the SH extratropics, the model total ozone shows a strong wave number 3 response rather than the wave number one dipole seen in the observations. A wave number 3 response is also evident in the 200 hPa geopotential height simulated by the model and in the NCEP analysis, and is consistent with the response in a linearised barotropic model forced in the Indonesian region. The different responses in the modelled and observed total ozone, suggest that tropopause effect is not the major factor in the SH extratropics, and it is likely that horizontal ozone transport also plays a role in this region. Despite a generally poor simulation of the zonal mean total ozone, the model was able to capture the anomalous strengthening of the SH stationary waves during austral spring of 1988, related to an intense stratosphere sudden warming. Received: 21 October 1996 / Accepted: 11 September 1997     

Are satellite products good proxies for gauge precipitation over Singapore?

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000–2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate model simulated future projections, when information on precipitation extremes need to be reliable as they are highly crucial for adaptation and mitigation.     

Trend analysis of air temperature time series in Greece and their relationship with circulation using surface and satellite data: 1955–2001

Summary In this study, trends of annual and seasonal surface air temperature time series were examined for 20 stations in Greece for the period 1955–2001, and satellite data for the period 1980–2001. Two statistical tests based on the least square method and one based on the Mann-Kendall test, which is also capable of detecting the starting year of possible climatic discontinuities or changes, were used for the analysis. Greece, in general, shows a cooling trend in winter for the period 1955–2001, whereas, summer shows an overall warming trend, however, neither is statistically significant. As a result, the overall trend of the annual values is nearly zero. Comparison with corresponding trends in the Northern Hemisphere (NH) shows that temperatures in Greece do not follow the intense warming trends. Satellite data indicate a remarkable warming trend in mean annual, winter and summer in Greece for the period 1980–2001, and a slight warming trend in annual, spring and autumn for the NH. Comparison with the respective trends detected in the surface air temperature for the same period (1980–2001) shows they match each other quite well in both Greece and the NH. The relationship between temperature variability in Greece and atmospheric circulation was also examined using correlation analysis with three circulation indices: the well-known North Atlantic Oscillation Index (NAOI), a Mediterranean Oscillation Index (MOI) and a new Mediterranean Circulation Index (MCI). The MOI and MCI indices show the most interesting correlation with winter temperatures in Greece. The behaviour of pressure and the height of the 500hPa surface over the Mediterranean region supports these results.     

Cloudiness over the Black Sea region in 1985–2009 from satellite data

The seasonal and interannual variability ofcloud fraction over the Black Sea region for the period of1985-2009 is analyzed using the CM SAF dataset obtained from the satellite measurements of a high-resolution AVHRR instrument. The features of geographic distribution and seasonal variations in cloudiness are investigated. The causes for its spatial inhomogeneity in different months are analyzed. It is demonstrated using the long-term dataset that the dramatic decrease in the amount of cloudiness occurred over the Black Sea region from 67% in 1985 to 54% in 2008. The value of the trend is -0.4% per year. Both the trends and the features of interannual variability of cloudiness, in particular, strongly pronounced four-year cycles, are in antiphase with variations in sea surface temperature. The cloudiness reduction accompanied by the increase in the influx of short-wave radiation may be the basic reason for the warming and sea surface temperature variations in the Black Sea region.     

Surface‐absorbed and top‐of‐atmosphere radiation fluxes for the Mackenzie River basin from satellite observations and a regional climate model and an evaluation of the model

Abstract

Both the earth‐reflected shortwave and outgoing longwave radiation (OLR) fluxes at the top of the atmosphere (TOA) as well as surface‐absorbed solar fluxes from Canadian Regional Climate Model (CRCM) simulations of the Mackenzie River Basin for the period March 2000 to September 2003 are compared with the radiation fluxes deduced from satellite observations. The differences between the model and satellite solar fluxes at the TOA and at the surface, which are used in this paper to evaluate the CRCM performance, have opposite biases under clear skies and overcast conditions, suggesting that the surface albedo is underestimated while cloud albedo is overestimated. The slightly larger differences between the model and satellite fluxes at the surface compared to those at the TOA indicate the existence of a small positive atmospheric absorption bias in the model. The persistent overestimation of TOA reflected solar fluxes and underestimation of the surface‐absorbed solar fluxes by the CRCM under all sky conditions are consistent with the overestimation of cloud fraction by the CRCM. This results in a larger shortwave cloud radiative forcing (CRF) both at the TOA and at the surface in the CRCM simulation. The OLR from the CRCM agrees well with the satellite observations except for persistent negative biases during the winter months under all sky conditions. Under clear skies, the OLR is slightly underestimated by the CRCM during the winter months and overestimated in the other months. Under overcast conditions the OLR is underestimated by the CRCM, suggesting an underestimation of cloud‐top temperature by the CRCM. There is an improvement in differences between model and satellite fluxes compared to previously reported results largely because of changes to the treatment of the surface in the model.     

Influence of natural and anthropogenic activities on UV Index variations – a study over tropical urban region using ground based observations and satellite data

Measurements of total ozone column and solar UV radiation under different atmospheric conditions are needed to define variations of both UV and ozone and to study the impact of ozone depletion at the Earth’s surface. In this study, spectral and broadband measurements of UV-B irradiance were obtained along with total ozone observations and aerosol optical depth measurements in the tropical urban region of Hyderabad, south India. We specifically used an Ultra-Violet Multifilter Rotating Shadow band Radiometer (UVMFR-SR), to measure UV irradiance in time and space. To assess the aerosol and O₃ effects on ground-reaching UV irradiance, we used measurements from a Microtops II sun photometer in addition to the Tropospheric Ultraviolet Visible radiation (TUV) model. We also assessed the Defense Meteorological Satellite Program – Operational Line Scanner (DMSP-OLS) night time satellite data for inferring biomass burning fires during the study period. Results clearly suggested a negative correlation between the DMSP-OLS satellite derived fire count data and UVMFR-SR data suggesting that aerosols from biomass burning are directly attenuating UV irradiance in the study region. Also, correlation analysis between UV index and ozone measurements from sun photometer and TOMS-Ozone Mapping Instrument (OMI) indicated a clear decrease in ground reaching UV-B irradiance during higher ozone conditions. The higher levels are attributed to photochemical production of O₃ during the oxidation of trace gases emitted from biomass burning. Results also suggested a relatively high attenuation in UV irradiance (~6% higher) from smoke particles than dust. We also found a relatively good agreement between the modeled (TUV) and measured UV irradiance spectra for different atmospheric conditions. Our results highlight the factors affecting UV irradiance in a tropical urban environment, south India.     

Observing upper troposphere–lower stratosphere climate with radio occultation data from the CHAMP satellite

High quality observations of the atmosphere are particularly required for monitoring global climate change. Radio occultation (RO) data, using Global Navigation Satellite System (GNSS) signals, are well suited for this challenge. The special climate utility of RO data arises from their long-term stability due to their self-calibrated nature. The German research satellite CHAllenging Minisatellite Payload for geoscientific research (CHAMP) continuously records RO profiles since August 2001 providing the first opportunity to create RO based climatologies for a multi-year period of more than 5 years. A period of missing CHAMP data from July 3, 2006 to August 8, 2006 can be bridged with RO data from the GRACE satellite (Gravity Recovery and Climate Experiment). We have built seasonal and zonal mean climatologies of atmospheric (dry) temperature, microwave refractivity, geopotential height and pressure with 10° latitudinal resolution. We show representative results with focus on dry temperatures and compare them with analysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Although we have available only about 150 CHAMP profiles per day (compared to millions of data entering the ECMWF analyses) the overall agreement between 8 and 30 km altitude is in general very good with systematic differences <0.5 K in most parts of the domain. Pronounced systematic differences (exceeding 2 K) in the tropical tropopause region and above Antarctica in southern winter can almost entirely be attributed to errors in the ECMWF analyses. Errors resulting from uneven sampling in space and time are a potential error source for single-satellite climatologies. The average CHAMP sampling error for seasonal zonal means is <0.2 K, higher values occur in restricted regions and time intervals which can be clearly identified by the sampling error estimation approach we introduced (which is based on ECMWF analysis fields). The total error of this new type of temperature climatologies is estimated to be <0.5 K below 30 km. The recently launched Taiwan/U.S. FORMOSAT-3/COSMIC constellation of 6 RO satellites started to provide thousands of RO profiles per day, but already now the single-satellite CHAMP RO climatologies improve upon modern operational climatologies in the upper troposphere–lower stratosphere and can act as absolute reference climatologies for validation of more bias-sensitive climate datasets and models.